Overview

Brought to you by YData

Dataset statistics

Number of variables67
Number of observations606772
Missing cells20145303
Missing cells (%)49.6%
Total size in memory310.2 MiB
Average record size in memory536.0 B

Variable types

Text67

Dataset

DescriptionEntomology NMNH Extant Specimen Records (USNM) 0052484-241126133413365
URLhttps://doi.org/10.15468/hnhrg3

Alerts

institutionID has constant value "urn:lsid:biocol.org:col:34871" Constant
collectionID has constant value "urn:uuid:18e3cd08-a962-4f0a-b72c-9a0b3600c5ad" Constant
institutionCode has constant value "USNM" Constant
collectionCode has constant value "ENT" Constant
datasetName has constant value "NMNH Extant Biology" Constant
verbatimDepth has constant value "220m inside cave entrance" Constant
verbatimCoordinateSystem has constant value "Degrees Minutes Seconds" Constant
kingdom has constant value "Animalia" Constant
catalogNumber has 234227 (38.6%) missing values Missing
recordNumber has 606735 (> 99.9%) missing values Missing
recordedBy has 204037 (33.6%) missing values Missing
sex has 340634 (56.1%) missing values Missing
lifeStage has 174721 (28.8%) missing values Missing
preparations has 42207 (7.0%) missing values Missing
associatedMedia has 391400 (64.5%) missing values Missing
occurrenceRemarks has 460889 (76.0%) missing values Missing
fieldNumber has 602507 (99.3%) missing values Missing
eventDate has 240191 (39.6%) missing values Missing
startDayOfYear has 245576 (40.5%) missing values Missing
endDayOfYear has 245088 (40.4%) missing values Missing
year has 240191 (39.6%) missing values Missing
month has 247434 (40.8%) missing values Missing
day has 271769 (44.8%) missing values Missing
verbatimEventDate has 397727 (65.5%) missing values Missing
habitat has 606573 (> 99.9%) missing values Missing
locationID has 605724 (99.8%) missing values Missing
higherGeography has 156606 (25.8%) missing values Missing
continent has 606644 (> 99.9%) missing values Missing
islandGroup has 604245 (99.6%) missing values Missing
island has 597364 (98.4%) missing values Missing
country has 156628 (25.8%) missing values Missing
stateProvince has 173815 (28.6%) missing values Missing
county has 255726 (42.1%) missing values Missing
locality has 158877 (26.2%) missing values Missing
minimumElevationInMeters has 559942 (92.3%) missing values Missing
maximumElevationInMeters has 575208 (94.8%) missing values Missing
verbatimElevation has 596798 (98.4%) missing values Missing
minimumDepthInMeters has 606738 (> 99.9%) missing values Missing
maximumDepthInMeters has 606761 (> 99.9%) missing values Missing
verbatimDepth has 606766 (> 99.9%) missing values Missing
decimalLatitude has 286669 (47.2%) missing values Missing
decimalLongitude has 286669 (47.2%) missing values Missing
geodeticDatum has 580298 (95.6%) missing values Missing
coordinateUncertaintyInMeters has 594787 (98.0%) missing values Missing
verbatimLatitude has 524830 (86.5%) missing values Missing
verbatimLongitude has 524799 (86.5%) missing values Missing
verbatimCoordinateSystem has 606771 (> 99.9%) missing values Missing
georeferenceProtocol has 368077 (60.7%) missing values Missing
georeferenceRemarks has 598295 (98.6%) missing values Missing
identificationQualifier has 605332 (99.8%) missing values Missing
typeStatus has 487787 (80.4%) missing values Missing
identifiedBy has 456553 (75.2%) missing values Missing
kingdom has 6321 (1.0%) missing values Missing
subgenus has 514262 (84.8%) missing values Missing
specificEpithet has 8782 (1.4%) missing values Missing
infraspecificEpithet has 573171 (94.5%) missing values Missing
taxonRank has 573176 (94.5%) missing values Missing
scientificNameAuthorship has 90810 (15.0%) missing values Missing
gbifID has unique values Unique
occurrenceID has unique values Unique

Reproduction

Analysis started2025-03-26 20:20:03.513319
Analysis finished2025-03-26 20:20:20.549284
Duration17.04 seconds
Software versionydata-profiling vv4.12.2
Download configurationconfig.json

Variables

gbifID
Text

Unique 

Distinct606772
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-03-26T16:20:20.824491image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters6067720
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique606772 ?
Unique (%)100.0%

Sample

1st row1321729650
2nd row1320180785
3rd row4403931423
4th row1320185860
5th row1320185980
ValueCountFrequency (%)
1321729650 1
 
< 0.1%
1320222196 1
 
< 0.1%
1321753851 1
 
< 0.1%
4403917418 1
 
< 0.1%
1321742115 1
 
< 0.1%
4403931423 1
 
< 0.1%
1320185860 1
 
< 0.1%
1320185980 1
 
< 0.1%
2236094411 1
 
< 0.1%
1320188725 1
 
< 0.1%
Other values (606762) 606762
> 99.9%
2025-03-26T16:20:21.192443image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1136782
18.7%
3 863457
14.2%
2 784593
12.9%
0 532377
8.8%
8 515717
8.5%
9 489863
8.1%
7 475707
7.8%
4 453377
 
7.5%
5 412057
 
6.8%
6 403790
 
6.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6067720
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 1136782
18.7%
3 863457
14.2%
2 784593
12.9%
0 532377
8.8%
8 515717
8.5%
9 489863
8.1%
7 475707
7.8%
4 453377
 
7.5%
5 412057
 
6.8%
6 403790
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6067720
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 1136782
18.7%
3 863457
14.2%
2 784593
12.9%
0 532377
8.8%
8 515717
8.5%
9 489863
8.1%
7 475707
7.8%
4 453377
 
7.5%
5 412057
 
6.8%
6 403790
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6067720
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 1136782
18.7%
3 863457
14.2%
2 784593
12.9%
0 532377
8.8%
8 515717
8.5%
9 489863
8.1%
7 475707
7.8%
4 453377
 
7.5%
5 412057
 
6.8%
6 403790
 
6.7%
Distinct56694
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-03-26T16:20:21.345134image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters11528668
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30841 ?
Unique (%)5.1%

Sample

1st row2013-09-16 11:56:00
2nd row2016-06-09 14:33:00
3rd row2023-08-23 09:36:00
4th row2023-05-19 10:32:00
5th row2015-10-05 15:58:00
ValueCountFrequency (%)
2023-05-13 60985
 
5.0%
2017-04-17 42669
 
3.5%
2014-01-09 31324
 
2.6%
2023-05-15 20609
 
1.7%
2023-05-12 16855
 
1.4%
2015-10-06 16031
 
1.3%
2018-02-08 14235
 
1.2%
2015-10-05 10298
 
0.8%
2017-09-29 10273
 
0.8%
11:48:00 10142
 
0.8%
Other values (3141) 980123
80.8%
2025-03-26T16:20:21.542827image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2938274
25.5%
1 1571709
13.6%
2 1377203
11.9%
- 1213544
10.5%
: 1213544
10.5%
606772
 
5.3%
3 595201
 
5.2%
5 496368
 
4.3%
4 458131
 
4.0%
9 315358
 
2.7%
Other values (3) 742564
 
6.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11528668
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 2938274
25.5%
1 1571709
13.6%
2 1377203
11.9%
- 1213544
10.5%
: 1213544
10.5%
606772
 
5.3%
3 595201
 
5.2%
5 496368
 
4.3%
4 458131
 
4.0%
9 315358
 
2.7%
Other values (3) 742564
 
6.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11528668
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 2938274
25.5%
1 1571709
13.6%
2 1377203
11.9%
- 1213544
10.5%
: 1213544
10.5%
606772
 
5.3%
3 595201
 
5.2%
5 496368
 
4.3%
4 458131
 
4.0%
9 315358
 
2.7%
Other values (3) 742564
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11528668
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 2938274
25.5%
1 1571709
13.6%
2 1377203
11.9%
- 1213544
10.5%
: 1213544
10.5%
606772
 
5.3%
3 595201
 
5.2%
5 496368
 
4.3%
4 458131
 
4.0%
9 315358
 
2.7%
Other values (3) 742564
 
6.4%

institutionID
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-03-26T16:20:21.584613image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length29
Median length29
Mean length29
Min length29

Characters and Unicode

Total characters17596388
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowurn:lsid:biocol.org:col:34871
2nd rowurn:lsid:biocol.org:col:34871
3rd rowurn:lsid:biocol.org:col:34871
4th rowurn:lsid:biocol.org:col:34871
5th rowurn:lsid:biocol.org:col:34871
ValueCountFrequency (%)
urn:lsid:biocol.org:col:34871 606772
100.0%
2025-03-26T16:20:21.662476image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 2427088
13.8%
: 2427088
13.8%
l 1820316
 
10.3%
i 1213544
 
6.9%
r 1213544
 
6.9%
c 1213544
 
6.9%
g 606772
 
3.4%
7 606772
 
3.4%
8 606772
 
3.4%
4 606772
 
3.4%
Other values (8) 4854176
27.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 17596388
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 2427088
13.8%
: 2427088
13.8%
l 1820316
 
10.3%
i 1213544
 
6.9%
r 1213544
 
6.9%
c 1213544
 
6.9%
g 606772
 
3.4%
7 606772
 
3.4%
8 606772
 
3.4%
4 606772
 
3.4%
Other values (8) 4854176
27.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 17596388
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 2427088
13.8%
: 2427088
13.8%
l 1820316
 
10.3%
i 1213544
 
6.9%
r 1213544
 
6.9%
c 1213544
 
6.9%
g 606772
 
3.4%
7 606772
 
3.4%
8 606772
 
3.4%
4 606772
 
3.4%
Other values (8) 4854176
27.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 17596388
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 2427088
13.8%
: 2427088
13.8%
l 1820316
 
10.3%
i 1213544
 
6.9%
r 1213544
 
6.9%
c 1213544
 
6.9%
g 606772
 
3.4%
7 606772
 
3.4%
8 606772
 
3.4%
4 606772
 
3.4%
Other values (8) 4854176
27.6%

collectionID
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-03-26T16:20:21.692003image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length45
Median length45
Mean length45
Min length45

Characters and Unicode

Total characters27304740
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowurn:uuid:18e3cd08-a962-4f0a-b72c-9a0b3600c5ad
2nd rowurn:uuid:18e3cd08-a962-4f0a-b72c-9a0b3600c5ad
3rd rowurn:uuid:18e3cd08-a962-4f0a-b72c-9a0b3600c5ad
4th rowurn:uuid:18e3cd08-a962-4f0a-b72c-9a0b3600c5ad
5th rowurn:uuid:18e3cd08-a962-4f0a-b72c-9a0b3600c5ad
ValueCountFrequency (%)
urn:uuid:18e3cd08-a962-4f0a-b72c-9a0b3600c5ad 606772
100.0%
2025-03-26T16:20:21.770228image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3033860
 
11.1%
a 2427088
 
8.9%
- 2427088
 
8.9%
d 1820316
 
6.7%
c 1820316
 
6.7%
u 1820316
 
6.7%
8 1213544
 
4.4%
3 1213544
 
4.4%
: 1213544
 
4.4%
9 1213544
 
4.4%
Other values (12) 9101580
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 27304740
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 3033860
 
11.1%
a 2427088
 
8.9%
- 2427088
 
8.9%
d 1820316
 
6.7%
c 1820316
 
6.7%
u 1820316
 
6.7%
8 1213544
 
4.4%
3 1213544
 
4.4%
: 1213544
 
4.4%
9 1213544
 
4.4%
Other values (12) 9101580
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 27304740
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 3033860
 
11.1%
a 2427088
 
8.9%
- 2427088
 
8.9%
d 1820316
 
6.7%
c 1820316
 
6.7%
u 1820316
 
6.7%
8 1213544
 
4.4%
3 1213544
 
4.4%
: 1213544
 
4.4%
9 1213544
 
4.4%
Other values (12) 9101580
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 27304740
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 3033860
 
11.1%
a 2427088
 
8.9%
- 2427088
 
8.9%
d 1820316
 
6.7%
c 1820316
 
6.7%
u 1820316
 
6.7%
8 1213544
 
4.4%
3 1213544
 
4.4%
: 1213544
 
4.4%
9 1213544
 
4.4%
Other values (12) 9101580
33.3%

institutionCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-03-26T16:20:21.798305image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters2427088
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUSNM
2nd rowUSNM
3rd rowUSNM
4th rowUSNM
5th rowUSNM
ValueCountFrequency (%)
usnm 606772
100.0%
2025-03-26T16:20:21.873960image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 606772
25.0%
S 606772
25.0%
N 606772
25.0%
M 606772
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2427088
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
U 606772
25.0%
S 606772
25.0%
N 606772
25.0%
M 606772
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2427088
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
U 606772
25.0%
S 606772
25.0%
N 606772
25.0%
M 606772
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2427088
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
U 606772
25.0%
S 606772
25.0%
N 606772
25.0%
M 606772
25.0%

collectionCode
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-03-26T16:20:21.901490image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1820316
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowENT
2nd rowENT
3rd rowENT
4th rowENT
5th rowENT
ValueCountFrequency (%)
ent 606772
100.0%
2025-03-26T16:20:21.979244image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 606772
33.3%
N 606772
33.3%
T 606772
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1820316
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 606772
33.3%
N 606772
33.3%
T 606772
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1820316
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 606772
33.3%
N 606772
33.3%
T 606772
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1820316
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 606772
33.3%
N 606772
33.3%
T 606772
33.3%

datasetName
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-03-26T16:20:22.006407image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters11528668
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNMNH Extant Biology
2nd rowNMNH Extant Biology
3rd rowNMNH Extant Biology
4th rowNMNH Extant Biology
5th rowNMNH Extant Biology
ValueCountFrequency (%)
nmnh 606772
33.3%
extant 606772
33.3%
biology 606772
33.3%
2025-03-26T16:20:22.084426image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1213544
 
10.5%
1213544
 
10.5%
t 1213544
 
10.5%
o 1213544
 
10.5%
M 606772
 
5.3%
H 606772
 
5.3%
E 606772
 
5.3%
x 606772
 
5.3%
a 606772
 
5.3%
n 606772
 
5.3%
Other values (5) 3033860
26.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11528668
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 1213544
 
10.5%
1213544
 
10.5%
t 1213544
 
10.5%
o 1213544
 
10.5%
M 606772
 
5.3%
H 606772
 
5.3%
E 606772
 
5.3%
x 606772
 
5.3%
a 606772
 
5.3%
n 606772
 
5.3%
Other values (5) 3033860
26.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11528668
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 1213544
 
10.5%
1213544
 
10.5%
t 1213544
 
10.5%
o 1213544
 
10.5%
M 606772
 
5.3%
H 606772
 
5.3%
E 606772
 
5.3%
x 606772
 
5.3%
a 606772
 
5.3%
n 606772
 
5.3%
Other values (5) 3033860
26.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11528668
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 1213544
 
10.5%
1213544
 
10.5%
t 1213544
 
10.5%
o 1213544
 
10.5%
M 606772
 
5.3%
H 606772
 
5.3%
E 606772
 
5.3%
x 606772
 
5.3%
a 606772
 
5.3%
n 606772
 
5.3%
Other values (5) 3033860
26.3%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-03-26T16:20:22.110743image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length17
Mean length16.99375054
Min length16

Characters and Unicode

Total characters10311332
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPreservedSpecimen
2nd rowPreservedSpecimen
3rd rowPreservedSpecimen
4th rowPreservedSpecimen
5th rowPreservedSpecimen
ValueCountFrequency (%)
preservedspecimen 602980
99.4%
humanobservation 3792
 
0.6%
2025-03-26T16:20:22.192979image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 3018692
29.3%
r 1209752
11.7%
n 610564
 
5.9%
i 606772
 
5.9%
s 606772
 
5.9%
v 606772
 
5.9%
m 606772
 
5.9%
c 602980
 
5.8%
P 602980
 
5.8%
p 602980
 
5.8%
Other values (9) 1236296
12.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10311332
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 3018692
29.3%
r 1209752
11.7%
n 610564
 
5.9%
i 606772
 
5.9%
s 606772
 
5.9%
v 606772
 
5.9%
m 606772
 
5.9%
c 602980
 
5.8%
P 602980
 
5.8%
p 602980
 
5.8%
Other values (9) 1236296
12.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10311332
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 3018692
29.3%
r 1209752
11.7%
n 610564
 
5.9%
i 606772
 
5.9%
s 606772
 
5.9%
v 606772
 
5.9%
m 606772
 
5.9%
c 602980
 
5.8%
P 602980
 
5.8%
p 602980
 
5.8%
Other values (9) 1236296
12.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10311332
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 3018692
29.3%
r 1209752
11.7%
n 610564
 
5.9%
i 606772
 
5.9%
s 606772
 
5.9%
v 606772
 
5.9%
m 606772
 
5.9%
c 602980
 
5.8%
P 602980
 
5.8%
p 602980
 
5.8%
Other values (9) 1236296
12.0%

occurrenceID
Text

Unique 

Distinct606772
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2025-03-26T16:20:22.437407image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length63
Median length63
Mean length63
Min length63

Characters and Unicode

Total characters38226636
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique606772 ?
Unique (%)100.0%

Sample

1st rowhttp://n2t.net/ark:/65665/3c83a10d1-1e59-4b08-af5b-28d12d2d0c80
2nd rowhttp://n2t.net/ark:/65665/383bb510d-d5ce-4c09-b4c4-bc1482fbaf28
3rd rowhttp://n2t.net/ark:/65665/383f13aa6-a5b6-40bc-bddc-b42c557aebfc
4th rowhttp://n2t.net/ark:/65665/383f4d560-c2d2-485c-906c-b6dad303fd7a
5th rowhttp://n2t.net/ark:/65665/383f634da-bb58-423c-85f4-a267b04c5ee5
ValueCountFrequency (%)
http://n2t.net/ark:/65665/3c83a10d1-1e59-4b08-af5b-28d12d2d0c80 1
 
< 0.1%
http://n2t.net/ark:/65665/3858e853e-4883-416b-a4b6-40f966e167d0 1
 
< 0.1%
http://n2t.net/ark:/65665/3c94d744a-d127-4564-9b0c-5d349a138dd0 1
 
< 0.1%
http://n2t.net/ark:/65665/384c3715b-7768-468a-b76b-a68ff7a554d0 1
 
< 0.1%
http://n2t.net/ark:/65665/3c8c6462b-a9e9-4efa-9205-6fb4e5ef4e65 1
 
< 0.1%
http://n2t.net/ark:/65665/383f13aa6-a5b6-40bc-bddc-b42c557aebfc 1
 
< 0.1%
http://n2t.net/ark:/65665/383f4d560-c2d2-485c-906c-b6dad303fd7a 1
 
< 0.1%
http://n2t.net/ark:/65665/383f634da-bb58-423c-85f4-a267b04c5ee5 1
 
< 0.1%
http://n2t.net/ark:/65665/3c898aee2-d463-49d7-ad9c-6fd423e170e1 1
 
< 0.1%
http://n2t.net/ark:/65665/38415675b-bf78-4cc9-8a52-eaed7e7b7339 1
 
< 0.1%
Other values (606762) 606762
> 99.9%
2025-03-26T16:20:22.779492image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 3033860
 
7.9%
6 2959749
 
7.7%
- 2427088
 
6.3%
t 2427088
 
6.3%
5 2351339
 
6.2%
a 1895919
 
5.0%
2 1745032
 
4.6%
e 1744367
 
4.6%
4 1743682
 
4.6%
3 1743457
 
4.6%
Other values (16) 16155055
42.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 38226636
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 3033860
 
7.9%
6 2959749
 
7.7%
- 2427088
 
6.3%
t 2427088
 
6.3%
5 2351339
 
6.2%
a 1895919
 
5.0%
2 1745032
 
4.6%
e 1744367
 
4.6%
4 1743682
 
4.6%
3 1743457
 
4.6%
Other values (16) 16155055
42.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 38226636
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 3033860
 
7.9%
6 2959749
 
7.7%
- 2427088
 
6.3%
t 2427088
 
6.3%
5 2351339
 
6.2%
a 1895919
 
5.0%
2 1745032
 
4.6%
e 1744367
 
4.6%
4 1743682
 
4.6%
3 1743457
 
4.6%
Other values (16) 16155055
42.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 38226636
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 3033860
 
7.9%
6 2959749
 
7.7%
- 2427088
 
6.3%
t 2427088
 
6.3%
5 2351339
 
6.2%
a 1895919
 
5.0%
2 1745032
 
4.6%
e 1744367
 
4.6%
4 1743682
 
4.6%
3 1743457
 
4.6%
Other values (16) 16155055
42.3%

catalogNumber
Text

Missing 

Distinct372531
Distinct (%)> 99.9%
Missing234227
Missing (%)38.6%
Memory size4.6 MiB
2025-03-26T16:20:22.990114image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length20
Median length15
Mean length15.03876579
Min length12

Characters and Unicode

Total characters5602617
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique372517 ?
Unique (%)> 99.9%

Sample

1st rowUSNMENT00831303
2nd rowUSNMENT00356408
3rd rowUSNMENT01436172
4th rowUSNMENT00357025
5th rowUSNMENT00314717
ValueCountFrequency (%)
usnment00935890 2
 
< 0.1%
usnment00533165 2
 
< 0.1%
usnment00377617 2
 
< 0.1%
usnment00536541 2
 
< 0.1%
usnment00377587 2
 
< 0.1%
usnment01200936 2
 
< 0.1%
usnment00385731 2
 
< 0.1%
usnment00937214 2
 
< 0.1%
usnment00935893 2
 
< 0.1%
usnment00937212 2
 
< 0.1%
Other values (372521) 372525
> 99.9%
2025-03-26T16:20:23.269447image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 807507
14.4%
N 744431
13.3%
1 378298
 
6.8%
S 372545
 
6.6%
U 372501
 
6.6%
M 372501
 
6.6%
E 371924
 
6.6%
T 371924
 
6.6%
3 303891
 
5.4%
4 226756
 
4.0%
Other values (11) 1280339
22.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5602617
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 807507
14.4%
N 744431
13.3%
1 378298
 
6.8%
S 372545
 
6.6%
U 372501
 
6.6%
M 372501
 
6.6%
E 371924
 
6.6%
T 371924
 
6.6%
3 303891
 
5.4%
4 226756
 
4.0%
Other values (11) 1280339
22.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5602617
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 807507
14.4%
N 744431
13.3%
1 378298
 
6.8%
S 372545
 
6.6%
U 372501
 
6.6%
M 372501
 
6.6%
E 371924
 
6.6%
T 371924
 
6.6%
3 303891
 
5.4%
4 226756
 
4.0%
Other values (11) 1280339
22.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5602617
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 807507
14.4%
N 744431
13.3%
1 378298
 
6.8%
S 372545
 
6.6%
U 372501
 
6.6%
M 372501
 
6.6%
E 371924
 
6.6%
T 371924
 
6.6%
3 303891
 
5.4%
4 226756
 
4.0%
Other values (11) 1280339
22.9%

recordNumber
Text

Missing 

Distinct33
Distinct (%)89.2%
Missing606735
Missing (%)> 99.9%
Memory size4.6 MiB
2025-03-26T16:20:23.347964image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length43
Median length21
Mean length17.35135135
Min length4

Characters and Unicode

Total characters642
Distinct characters57
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)86.5%

Sample

1st rowCollection number "14,957"
2nd rowLot 607, Sub 182
3rd row4012
4th rowDognin Collection
5th row12.097
ValueCountFrequency (%)
collection 10
 
10.0%
no 9
 
9.0%
walsingham 7
 
7.0%
dognin 5
 
5.0%
hopkins 3
 
3.0%
quaintance 2
 
2.0%
wlsm 2
 
2.0%
townes 2
 
2.0%
number 2
 
2.0%
from 2
 
2.0%
Other values (56) 56
56.0%
2025-03-26T16:20:23.472231image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
63
 
9.8%
o 52
 
8.1%
n 47
 
7.3%
l 39
 
6.1%
i 33
 
5.1%
. 26
 
4.0%
e 25
 
3.9%
a 22
 
3.4%
1 19
 
3.0%
t 19
 
3.0%
Other values (47) 297
46.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 642
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
63
 
9.8%
o 52
 
8.1%
n 47
 
7.3%
l 39
 
6.1%
i 33
 
5.1%
. 26
 
4.0%
e 25
 
3.9%
a 22
 
3.4%
1 19
 
3.0%
t 19
 
3.0%
Other values (47) 297
46.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 642
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
63
 
9.8%
o 52
 
8.1%
n 47
 
7.3%
l 39
 
6.1%
i 33
 
5.1%
. 26
 
4.0%
e 25
 
3.9%
a 22
 
3.4%
1 19
 
3.0%
t 19
 
3.0%
Other values (47) 297
46.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 642
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
63
 
9.8%
o 52
 
8.1%
n 47
 
7.3%
l 39
 
6.1%
i 33
 
5.1%
. 26
 
4.0%
e 25
 
3.9%
a 22
 
3.4%
1 19
 
3.0%
t 19
 
3.0%
Other values (47) 297
46.3%

recordedBy
Text

Missing 

Distinct18760
Distinct (%)4.7%
Missing204037
Missing (%)33.6%
Memory size4.6 MiB
2025-03-26T16:20:23.600394image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length90
Median length84
Mean length11.2569208
Min length1

Characters and Unicode

Total characters4533556
Distinct characters84
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9115 ?
Unique (%)2.3%

Sample

1st rowM. Ortiz B.
2nd row[Not Stated]
3rd rowS. Roble
4th row[Not Stated]
5th rowC. Flint
ValueCountFrequency (%)
not 65951
 
7.2%
stated 65935
 
7.2%
l 40315
 
4.4%
40014
 
4.4%
j 37035
 
4.0%
macior 31334
 
3.4%
d 28567
 
3.1%
c 27248
 
3.0%
r 25726
 
2.8%
b 22129
 
2.4%
Other values (10706) 532679
58.1%
2025-03-26T16:20:23.806633image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
514198
 
11.3%
. 356796
 
7.9%
t 306230
 
6.8%
a 300488
 
6.6%
e 291123
 
6.4%
o 241004
 
5.3%
r 230155
 
5.1%
i 174375
 
3.8%
n 170484
 
3.8%
l 137338
 
3.0%
Other values (74) 1811365
40.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4533556
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
514198
 
11.3%
. 356796
 
7.9%
t 306230
 
6.8%
a 300488
 
6.6%
e 291123
 
6.4%
o 241004
 
5.3%
r 230155
 
5.1%
i 174375
 
3.8%
n 170484
 
3.8%
l 137338
 
3.0%
Other values (74) 1811365
40.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4533556
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
514198
 
11.3%
. 356796
 
7.9%
t 306230
 
6.8%
a 300488
 
6.6%
e 291123
 
6.4%
o 241004
 
5.3%
r 230155
 
5.1%
i 174375
 
3.8%
n 170484
 
3.8%
l 137338
 
3.0%
Other values (74) 1811365
40.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4533556
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
514198
 
11.3%
. 356796
 
7.9%
t 306230
 
6.8%
a 300488
 
6.6%
e 291123
 
6.4%
o 241004
 
5.3%
r 230155
 
5.1%
i 174375
 
3.8%
n 170484
 
3.8%
l 137338
 
3.0%
Other values (74) 1811365
40.0%
Distinct944
Distinct (%)0.2%
Missing3147
Missing (%)0.5%
Memory size4.6 MiB
2025-03-26T16:20:23.843223image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length1
Mean length1.0448772
Min length1

Characters and Unicode

Total characters630714
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique396 ?
Unique (%)0.1%

Sample

1st row7
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 550160
91.1%
2 10299
 
1.7%
3 6642
 
1.1%
4 4313
 
0.7%
5 2628
 
0.4%
6 2350
 
0.4%
7 1829
 
0.3%
8 1535
 
0.3%
10 1307
 
0.2%
9 1256
 
0.2%
Other values (934) 21306
 
3.5%
2025-03-26T16:20:23.930698image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 562791
89.2%
2 17694
 
2.8%
3 11847
 
1.9%
4 8369
 
1.3%
5 6535
 
1.0%
0 6158
 
1.0%
6 5369
 
0.9%
7 4438
 
0.7%
8 4010
 
0.6%
9 3503
 
0.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 630714
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 562791
89.2%
2 17694
 
2.8%
3 11847
 
1.9%
4 8369
 
1.3%
5 6535
 
1.0%
0 6158
 
1.0%
6 5369
 
0.9%
7 4438
 
0.7%
8 4010
 
0.6%
9 3503
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 630714
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 562791
89.2%
2 17694
 
2.8%
3 11847
 
1.9%
4 8369
 
1.3%
5 6535
 
1.0%
0 6158
 
1.0%
6 5369
 
0.9%
7 4438
 
0.7%
8 4010
 
0.6%
9 3503
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 630714
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 562791
89.2%
2 17694
 
2.8%
3 11847
 
1.9%
4 8369
 
1.3%
5 6535
 
1.0%
0 6158
 
1.0%
6 5369
 
0.9%
7 4438
 
0.7%
8 4010
 
0.6%
9 3503
 
0.6%

sex
Text

Missing 

Distinct95
Distinct (%)< 0.1%
Missing340634
Missing (%)56.1%
Memory size4.6 MiB
2025-03-26T16:20:23.960178image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length40
Median length34
Mean length5.351866325
Min length4

Characters and Unicode

Total characters1424335
Distinct characters23
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)< 0.1%

Sample

1st rowWorker
2nd rowMale
3rd rowMale
4th rowMale
5th rowMale
ValueCountFrequency (%)
male 138316
50.2%
female 93556
34.0%
unknown 34157
 
12.4%
worker 7048
 
2.6%
1493
 
0.5%
unable 241
 
0.1%
to 241
 
0.1%
determine 241
 
0.1%
2025-03-26T16:20:24.055102image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 333440
23.4%
l 232113
16.3%
a 232113
16.3%
M 121133
 
8.5%
m 110980
 
7.8%
n 102953
 
7.2%
F 80877
 
5.7%
o 41446
 
2.9%
k 41205
 
2.9%
U 34343
 
2.4%
Other values (13) 93732
 
6.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1424335
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 333440
23.4%
l 232113
16.3%
a 232113
16.3%
M 121133
 
8.5%
m 110980
 
7.8%
n 102953
 
7.2%
F 80877
 
5.7%
o 41446
 
2.9%
k 41205
 
2.9%
U 34343
 
2.4%
Other values (13) 93732
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1424335
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 333440
23.4%
l 232113
16.3%
a 232113
16.3%
M 121133
 
8.5%
m 110980
 
7.8%
n 102953
 
7.2%
F 80877
 
5.7%
o 41446
 
2.9%
k 41205
 
2.9%
U 34343
 
2.4%
Other values (13) 93732
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1424335
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 333440
23.4%
l 232113
16.3%
a 232113
16.3%
M 121133
 
8.5%
m 110980
 
7.8%
n 102953
 
7.2%
F 80877
 
5.7%
o 41446
 
2.9%
k 41205
 
2.9%
U 34343
 
2.4%
Other values (13) 93732
 
6.6%

lifeStage
Text

Missing 

Distinct178
Distinct (%)< 0.1%
Missing174721
Missing (%)28.8%
Memory size4.6 MiB
2025-03-26T16:20:24.085382image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length59
Median length5
Mean length5.285362145
Min length1

Characters and Unicode

Total characters2283546
Distinct characters45
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)< 0.1%

Sample

1st rowAdult
2nd rowAdult
3rd rowAdult
4th rowAdult
5th rowAdult
ValueCountFrequency (%)
adult 426544
95.7%
immature 4891
 
1.1%
wings 3379
 
0.8%
alate 1664
 
0.4%
apterous 1578
 
0.4%
pupa 1203
 
0.3%
soldier 1085
 
0.2%
worker 1013
 
0.2%
larva 944
 
0.2%
reproductive 670
 
0.2%
Other values (46) 2948
 
0.7%
2025-03-26T16:20:24.182537image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 436165
19.1%
u 435758
19.1%
l 430026
18.8%
d 428404
18.8%
A 393574
17.2%
a 47339
 
2.1%
13868
 
0.6%
e 13637
 
0.6%
r 11733
 
0.5%
m 10529
 
0.5%
Other values (35) 62513
 
2.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2283546
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 436165
19.1%
u 435758
19.1%
l 430026
18.8%
d 428404
18.8%
A 393574
17.2%
a 47339
 
2.1%
13868
 
0.6%
e 13637
 
0.6%
r 11733
 
0.5%
m 10529
 
0.5%
Other values (35) 62513
 
2.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2283546
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 436165
19.1%
u 435758
19.1%
l 430026
18.8%
d 428404
18.8%
A 393574
17.2%
a 47339
 
2.1%
13868
 
0.6%
e 13637
 
0.6%
r 11733
 
0.5%
m 10529
 
0.5%
Other values (35) 62513
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2283546
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 436165
19.1%
u 435758
19.1%
l 430026
18.8%
d 428404
18.8%
A 393574
17.2%
a 47339
 
2.1%
13868
 
0.6%
e 13637
 
0.6%
r 11733
 
0.5%
m 10529
 
0.5%
Other values (35) 62513
 
2.7%

preparations
Text

Missing 

Distinct273
Distinct (%)< 0.1%
Missing42207
Missing (%)7.0%
Memory size4.6 MiB
2025-03-26T16:20:24.211395image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length93
Median length6
Mean length6.840454155
Min length1

Characters and Unicode

Total characters3861881
Distinct characters58
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique113 ?
Unique (%)< 0.1%

Sample

1st rowPinned
2nd rowPinned
3rd rowPinned
4th rowEnvelope
5th rowPinned
ValueCountFrequency (%)
pinned 391095
63.9%
envelope 115104
 
18.8%
slide 65322
 
10.7%
vial 9525
 
1.6%
ethanol 6498
 
1.1%
section 3762
 
0.6%
on 3666
 
0.6%
3207
 
0.5%
ink 3164
 
0.5%
pen 3084
 
0.5%
Other values (93) 7827
 
1.3%
2025-03-26T16:20:24.302519image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 919664
23.8%
e 703690
18.2%
i 474335
12.3%
d 457517
11.8%
P 367458
 
9.5%
l 200510
 
5.2%
p 143329
 
3.7%
o 134368
 
3.5%
v 115269
 
3.0%
E 113289
 
2.9%
Other values (48) 232452
 
6.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3861881
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 919664
23.8%
e 703690
18.2%
i 474335
12.3%
d 457517
11.8%
P 367458
 
9.5%
l 200510
 
5.2%
p 143329
 
3.7%
o 134368
 
3.5%
v 115269
 
3.0%
E 113289
 
2.9%
Other values (48) 232452
 
6.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3861881
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 919664
23.8%
e 703690
18.2%
i 474335
12.3%
d 457517
11.8%
P 367458
 
9.5%
l 200510
 
5.2%
p 143329
 
3.7%
o 134368
 
3.5%
v 115269
 
3.0%
E 113289
 
2.9%
Other values (48) 232452
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3861881
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 919664
23.8%
e 703690
18.2%
i 474335
12.3%
d 457517
11.8%
P 367458
 
9.5%
l 200510
 
5.2%
p 143329
 
3.7%
o 134368
 
3.5%
v 115269
 
3.0%
E 113289
 
2.9%
Other values (48) 232452
 
6.0%

associatedMedia
Text

Missing 

Distinct215150
Distinct (%)99.9%
Missing391400
Missing (%)64.5%
Memory size4.6 MiB
2025-03-26T16:20:24.437465image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length259
Median length49
Mean length52.23278328
Min length48

Characters and Unicode

Total characters11249479
Distinct characters31
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique215010 ?
Unique (%)99.8%

Sample

1st rowhttps://collections.nmnh.si.edu/media/?i=16421668
2nd rowhttps://collections.nmnh.si.edu/media/?i=16411146
3rd rowhttps://collections.nmnh.si.edu/media/?i=16342640
4th rowhttps://collections.nmnh.si.edu/media/?i=16365128
5th rowhttps://collections.nmnh.si.edu/media/?i=16326001
ValueCountFrequency (%)
https://collections.nmnh.si.edu/media/?i=16612365 38
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=16556913 19
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=16558066 14
 
< 0.1%
16556913 12
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=16623013 10
 
< 0.1%
16574611 9
 
< 0.1%
https://collections.nmnh.si.edu/media/?i=16945972 7
 
< 0.1%
16561531 7
 
< 0.1%
16556901 7
 
< 0.1%
16552041 5
 
< 0.1%
Other values (284987) 288121
> 99.9%
2025-03-26T16:20:24.643754image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 861488
 
7.7%
/ 861488
 
7.7%
e 646116
 
5.7%
t 646116
 
5.7%
s 646116
 
5.7%
. 646116
 
5.7%
n 646116
 
5.7%
1 469558
 
4.2%
l 430744
 
3.8%
o 430744
 
3.8%
Other values (21) 4964877
44.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11249479
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 861488
 
7.7%
/ 861488
 
7.7%
e 646116
 
5.7%
t 646116
 
5.7%
s 646116
 
5.7%
. 646116
 
5.7%
n 646116
 
5.7%
1 469558
 
4.2%
l 430744
 
3.8%
o 430744
 
3.8%
Other values (21) 4964877
44.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11249479
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 861488
 
7.7%
/ 861488
 
7.7%
e 646116
 
5.7%
t 646116
 
5.7%
s 646116
 
5.7%
. 646116
 
5.7%
n 646116
 
5.7%
1 469558
 
4.2%
l 430744
 
3.8%
o 430744
 
3.8%
Other values (21) 4964877
44.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11249479
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 861488
 
7.7%
/ 861488
 
7.7%
e 646116
 
5.7%
t 646116
 
5.7%
s 646116
 
5.7%
. 646116
 
5.7%
n 646116
 
5.7%
1 469558
 
4.2%
l 430744
 
3.8%
o 430744
 
3.8%
Other values (21) 4964877
44.1%

occurrenceRemarks
Text

Missing 

Distinct31335
Distinct (%)21.5%
Missing460889
Missing (%)76.0%
Memory size4.6 MiB
2025-03-26T16:20:24.787963image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4510
Median length3868
Mean length74.77600543
Min length1

Characters and Unicode

Total characters10908548
Distinct characters117
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27594 ?
Unique (%)18.9%

Sample

1st rowOne leg removed for genetic sampling while on loan to GUELPH.
2nd rowLindroth, 1975:125: (the loc. is no doubt wrong).
3rd rowF. Monros Coll. 1959 G.M. Greene Coll. C. Schaeffer Coll. Shoemaker Coll. 1956 A. Nicolay Coll. 1950 L.W. Saylor Coll.
4th rowSpecimen data is incomplete. Phase 1 of data capture inlcluded USNMENT#s and general locality.
5th rowOne leg removed for genetic sampling while on loan to GUELPH.
ValueCountFrequency (%)
digitization 56354
 
3.4%
by 48279
 
3.0%
digital 44182
 
2.7%
transcribed 44146
 
2.7%
volunteers 44146
 
2.7%
of 42619
 
2.6%
on 41122
 
2.5%
to 36884
 
2.3%
loan 36586
 
2.2%
for 36346
 
2.2%
Other values (41907) 1205668
73.7%
2025-03-26T16:20:25.011323image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1490449
 
13.7%
e 818612
 
7.5%
i 792230
 
7.3%
t 655175
 
6.0%
a 654239
 
6.0%
o 640885
 
5.9%
n 603192
 
5.5%
r 544239
 
5.0%
s 442305
 
4.1%
l 420489
 
3.9%
Other values (107) 3846733
35.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10908548
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1490449
 
13.7%
e 818612
 
7.5%
i 792230
 
7.3%
t 655175
 
6.0%
a 654239
 
6.0%
o 640885
 
5.9%
n 603192
 
5.5%
r 544239
 
5.0%
s 442305
 
4.1%
l 420489
 
3.9%
Other values (107) 3846733
35.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10908548
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1490449
 
13.7%
e 818612
 
7.5%
i 792230
 
7.3%
t 655175
 
6.0%
a 654239
 
6.0%
o 640885
 
5.9%
n 603192
 
5.5%
r 544239
 
5.0%
s 442305
 
4.1%
l 420489
 
3.9%
Other values (107) 3846733
35.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10908548
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1490449
 
13.7%
e 818612
 
7.5%
i 792230
 
7.3%
t 655175
 
6.0%
a 654239
 
6.0%
o 640885
 
5.9%
n 603192
 
5.5%
r 544239
 
5.0%
s 442305
 
4.1%
l 420489
 
3.9%
Other values (107) 3846733
35.3%

fieldNumber
Text

Missing 

Distinct3099
Distinct (%)72.7%
Missing602507
Missing (%)99.3%
Memory size4.6 MiB
2025-03-26T16:20:25.135319image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length29
Mean length9.594841735
Min length1

Characters and Unicode

Total characters40922
Distinct characters70
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2651 ?
Unique (%)62.2%

Sample

1st rowBBB991
2nd rowBBB642-DERM
3rd row1653
4th rowJSL021109-18
5th rowCOL-8-101
ValueCountFrequency (%)
1653 128
 
2.8%
2 46
 
1.0%
bbb899-hym 34
 
0.7%
1 32
 
0.7%
bbb791-hym 26
 
0.6%
bbb749-hym 23
 
0.5%
759-8 22
 
0.5%
tub 20
 
0.4%
tank 18
 
0.4%
olym-net-11 18
 
0.4%
Other values (3095) 4240
92.0%
2025-03-26T16:20:25.318007image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
B 4806
 
11.7%
0 4010
 
9.8%
- 3998
 
9.8%
1 3409
 
8.3%
2 2245
 
5.5%
3 1566
 
3.8%
6 1547
 
3.8%
7 1515
 
3.7%
4 1503
 
3.7%
9 1485
 
3.6%
Other values (60) 14838
36.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 40922
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
B 4806
 
11.7%
0 4010
 
9.8%
- 3998
 
9.8%
1 3409
 
8.3%
2 2245
 
5.5%
3 1566
 
3.8%
6 1547
 
3.8%
7 1515
 
3.7%
4 1503
 
3.7%
9 1485
 
3.6%
Other values (60) 14838
36.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 40922
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
B 4806
 
11.7%
0 4010
 
9.8%
- 3998
 
9.8%
1 3409
 
8.3%
2 2245
 
5.5%
3 1566
 
3.8%
6 1547
 
3.8%
7 1515
 
3.7%
4 1503
 
3.7%
9 1485
 
3.6%
Other values (60) 14838
36.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 40922
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
B 4806
 
11.7%
0 4010
 
9.8%
- 3998
 
9.8%
1 3409
 
8.3%
2 2245
 
5.5%
3 1566
 
3.8%
6 1547
 
3.8%
7 1515
 
3.7%
4 1503
 
3.7%
9 1485
 
3.6%
Other values (60) 14838
36.3%

eventDate
Text

Missing 

Distinct46197
Distinct (%)12.6%
Missing240191
Missing (%)39.6%
Memory size4.6 MiB
2025-03-26T16:20:25.420911image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length10
Mean length11.06853056
Min length4

Characters and Unicode

Total characters4057513
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13232 ?
Unique (%)3.6%

Sample

1st row1967-06-20
2nd row1914-07
3rd row2005-08-02
4th row1964-04-25
5th row1971-08-22
ValueCountFrequency (%)
1998-07-26 713
 
0.2%
1938 575
 
0.2%
2006-06-24 545
 
0.1%
1933 525
 
0.1%
1960-06-30 508
 
0.1%
1936 473
 
0.1%
1927-07-10 471
 
0.1%
1964-08-01/1964-08-31 450
 
0.1%
1930 435
 
0.1%
1966-06-23 411
 
0.1%
Other values (46179) 361509
98.6%
2025-03-26T16:20:25.590075image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 785361
19.4%
1 704777
17.4%
0 655387
16.2%
9 494685
12.2%
2 289127
 
7.1%
6 226268
 
5.6%
7 217403
 
5.4%
8 184194
 
4.5%
5 160294
 
4.0%
3 156464
 
3.9%
Other values (6) 183553
 
4.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4057513
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
- 785361
19.4%
1 704777
17.4%
0 655387
16.2%
9 494685
12.2%
2 289127
 
7.1%
6 226268
 
5.6%
7 217403
 
5.4%
8 184194
 
4.5%
5 160294
 
4.0%
3 156464
 
3.9%
Other values (6) 183553
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4057513
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
- 785361
19.4%
1 704777
17.4%
0 655387
16.2%
9 494685
12.2%
2 289127
 
7.1%
6 226268
 
5.6%
7 217403
 
5.4%
8 184194
 
4.5%
5 160294
 
4.0%
3 156464
 
3.9%
Other values (6) 183553
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4057513
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
- 785361
19.4%
1 704777
17.4%
0 655387
16.2%
9 494685
12.2%
2 289127
 
7.1%
6 226268
 
5.6%
7 217403
 
5.4%
8 184194
 
4.5%
5 160294
 
4.0%
3 156464
 
3.9%
Other values (6) 183553
 
4.5%

startDayOfYear
Text

Missing 

Distinct366
Distinct (%)0.1%
Missing245576
Missing (%)40.5%
Memory size4.6 MiB
2025-03-26T16:20:25.730414image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.849070865
Min length1

Characters and Unicode

Total characters1029073
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row171
2nd row212
3rd row214
4th row116
5th row234
ValueCountFrequency (%)
212 4216
 
1.2%
213 4030
 
1.1%
182 3961
 
1.1%
181 3456
 
1.0%
151 3121
 
0.9%
152 2953
 
0.8%
183 2920
 
0.8%
191 2891
 
0.8%
207 2752
 
0.8%
178 2644
 
0.7%
Other values (356) 328252
90.9%
2025-03-26T16:20:25.930560image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 238953
23.2%
2 203241
19.7%
3 101054
9.8%
9 71235
 
6.9%
0 71206
 
6.9%
4 70387
 
6.8%
5 69608
 
6.8%
8 68690
 
6.7%
6 68141
 
6.6%
7 66558
 
6.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1029073
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 238953
23.2%
2 203241
19.7%
3 101054
9.8%
9 71235
 
6.9%
0 71206
 
6.9%
4 70387
 
6.8%
5 69608
 
6.8%
8 68690
 
6.7%
6 68141
 
6.6%
7 66558
 
6.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1029073
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 238953
23.2%
2 203241
19.7%
3 101054
9.8%
9 71235
 
6.9%
0 71206
 
6.9%
4 70387
 
6.8%
5 69608
 
6.8%
8 68690
 
6.7%
6 68141
 
6.6%
7 66558
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1029073
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 238953
23.2%
2 203241
19.7%
3 101054
9.8%
9 71235
 
6.9%
0 71206
 
6.9%
4 70387
 
6.8%
5 69608
 
6.8%
8 68690
 
6.7%
6 68141
 
6.6%
7 66558
 
6.5%

endDayOfYear
Text

Missing 

Distinct366
Distinct (%)0.1%
Missing245088
Missing (%)40.4%
Memory size4.6 MiB
2025-03-26T16:20:26.071187image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.857237257
Min length1

Characters and Unicode

Total characters1033417
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row171
2nd row212
3rd row214
4th row116
5th row234
ValueCountFrequency (%)
212 5004
 
1.4%
181 4292
 
1.2%
213 3681
 
1.0%
151 3542
 
1.0%
182 3378
 
0.9%
243 3195
 
0.9%
207 3009
 
0.8%
191 2957
 
0.8%
197 2789
 
0.8%
120 2634
 
0.7%
Other values (356) 327203
90.5%
2025-03-26T16:20:26.278340image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 237644
23.0%
2 203333
19.7%
3 102497
9.9%
0 72304
 
7.0%
9 72028
 
7.0%
4 70495
 
6.8%
5 70090
 
6.8%
6 68897
 
6.7%
7 68205
 
6.6%
8 67924
 
6.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1033417
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 237644
23.0%
2 203333
19.7%
3 102497
9.9%
0 72304
 
7.0%
9 72028
 
7.0%
4 70495
 
6.8%
5 70090
 
6.8%
6 68897
 
6.7%
7 68205
 
6.6%
8 67924
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1033417
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 237644
23.0%
2 203333
19.7%
3 102497
9.9%
0 72304
 
7.0%
9 72028
 
7.0%
4 70495
 
6.8%
5 70090
 
6.8%
6 68897
 
6.7%
7 68205
 
6.6%
8 67924
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1033417
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 237644
23.0%
2 203333
19.7%
3 102497
9.9%
0 72304
 
7.0%
9 72028
 
7.0%
4 70495
 
6.8%
5 70090
 
6.8%
6 68897
 
6.7%
7 68205
 
6.6%
8 67924
 
6.6%

year
Text

Missing 

Distinct191
Distinct (%)0.1%
Missing240191
Missing (%)39.6%
Memory size4.6 MiB
2025-03-26T16:20:26.396081image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters1466324
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)< 0.1%

Sample

1st row1967
2nd row1914
3rd row2005
4th row1964
5th row1971
ValueCountFrequency (%)
1966 12350
 
3.4%
1968 9217
 
2.5%
1971 8998
 
2.5%
1967 8387
 
2.3%
1965 7909
 
2.2%
1972 6300
 
1.7%
1964 6168
 
1.7%
1974 6110
 
1.7%
1973 6101
 
1.7%
1963 5587
 
1.5%
Other values (181) 289454
79.0%
2025-03-26T16:20:26.563348image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 399599
27.3%
9 383178
26.1%
6 109131
 
7.4%
0 108434
 
7.4%
2 93263
 
6.4%
7 89574
 
6.1%
8 75173
 
5.1%
5 72714
 
5.0%
3 69947
 
4.8%
4 65311
 
4.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1466324
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 399599
27.3%
9 383178
26.1%
6 109131
 
7.4%
0 108434
 
7.4%
2 93263
 
6.4%
7 89574
 
6.1%
8 75173
 
5.1%
5 72714
 
5.0%
3 69947
 
4.8%
4 65311
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1466324
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 399599
27.3%
9 383178
26.1%
6 109131
 
7.4%
0 108434
 
7.4%
2 93263
 
6.4%
7 89574
 
6.1%
8 75173
 
5.1%
5 72714
 
5.0%
3 69947
 
4.8%
4 65311
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1466324
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 399599
27.3%
9 383178
26.1%
6 109131
 
7.4%
0 108434
 
7.4%
2 93263
 
6.4%
7 89574
 
6.1%
8 75173
 
5.1%
5 72714
 
5.0%
3 69947
 
4.8%
4 65311
 
4.5%

month
Text

Missing 

Distinct12
Distinct (%)< 0.1%
Missing247434
Missing (%)40.8%
Memory size4.6 MiB
2025-03-26T16:20:26.605542image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.113244355
Min length1

Characters and Unicode

Total characters400031
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row6
2nd row7
3rd row8
4th row4
5th row8
ValueCountFrequency (%)
7 74327
20.7%
6 59155
16.5%
8 52131
14.5%
5 36375
10.1%
9 26135
 
7.3%
4 25848
 
7.2%
3 16958
 
4.7%
10 16606
 
4.6%
2 14464
 
4.0%
11 13789
 
3.8%
Other values (2) 23550
 
6.6%
2025-03-26T16:20:26.689302image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 74327
18.6%
1 67734
16.9%
6 59155
14.8%
8 52131
13.0%
5 36375
9.1%
9 26135
 
6.5%
4 25848
 
6.5%
2 24762
 
6.2%
3 16958
 
4.2%
0 16606
 
4.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 400031
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
7 74327
18.6%
1 67734
16.9%
6 59155
14.8%
8 52131
13.0%
5 36375
9.1%
9 26135
 
6.5%
4 25848
 
6.5%
2 24762
 
6.2%
3 16958
 
4.2%
0 16606
 
4.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 400031
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
7 74327
18.6%
1 67734
16.9%
6 59155
14.8%
8 52131
13.0%
5 36375
9.1%
9 26135
 
6.5%
4 25848
 
6.5%
2 24762
 
6.2%
3 16958
 
4.2%
0 16606
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 400031
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
7 74327
18.6%
1 67734
16.9%
6 59155
14.8%
8 52131
13.0%
5 36375
9.1%
9 26135
 
6.5%
4 25848
 
6.5%
2 24762
 
6.2%
3 16958
 
4.2%
0 16606
 
4.2%

day
Text

Missing 

Distinct31
Distinct (%)< 0.1%
Missing271769
Missing (%)44.8%
Memory size4.6 MiB
2025-03-26T16:20:26.732590image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.68309836
Min length1

Characters and Unicode

Total characters563843
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20
2nd row2
3rd row25
4th row22
5th row6
ValueCountFrequency (%)
1 20625
 
6.2%
8 13079
 
3.9%
20 12232
 
3.7%
10 12032
 
3.6%
15 11926
 
3.6%
12 11913
 
3.6%
25 11288
 
3.4%
6 11192
 
3.3%
16 11188
 
3.3%
23 10889
 
3.3%
Other values (21) 208639
62.3%
2025-03-26T16:20:26.827319image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 156112
27.7%
2 138233
24.5%
3 45296
 
8.0%
8 33345
 
5.9%
0 33284
 
5.9%
5 33267
 
5.9%
6 32950
 
5.8%
4 31623
 
5.6%
7 30970
 
5.5%
9 28763
 
5.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 563843
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 156112
27.7%
2 138233
24.5%
3 45296
 
8.0%
8 33345
 
5.9%
0 33284
 
5.9%
5 33267
 
5.9%
6 32950
 
5.8%
4 31623
 
5.6%
7 30970
 
5.5%
9 28763
 
5.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 563843
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 156112
27.7%
2 138233
24.5%
3 45296
 
8.0%
8 33345
 
5.9%
0 33284
 
5.9%
5 33267
 
5.9%
6 32950
 
5.8%
4 31623
 
5.6%
7 30970
 
5.5%
9 28763
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 563843
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 156112
27.7%
2 138233
24.5%
3 45296
 
8.0%
8 33345
 
5.9%
0 33284
 
5.9%
5 33267
 
5.9%
6 32950
 
5.8%
4 31623
 
5.6%
7 30970
 
5.5%
9 28763
 
5.1%

verbatimEventDate
Text

Missing 

Distinct68194
Distinct (%)32.6%
Missing397727
Missing (%)65.5%
Memory size4.6 MiB
2025-03-26T16:20:26.961068image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length79
Median length71
Mean length10.59761295
Min length1

Characters and Unicode

Total characters2215378
Distinct characters92
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51734 ?
Unique (%)24.7%

Sample

1st row[Not Stated]
2nd row2-Aug-2005
3rd row[Not Stated]
4th row[Not Stated]
5th row9-IX-78
ValueCountFrequency (%)
not 32302
 
8.2%
stated 32270
 
8.2%
july 8734
 
2.2%
aug 7763
 
2.0%
june 7249
 
1.8%
may 5981
 
1.5%
1968 5777
 
1.5%
1971 5725
 
1.5%
1966 4517
 
1.1%
1972 2988
 
0.8%
Other values (37418) 280736
71.2%
2025-03-26T16:20:27.180234image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 218059
 
9.8%
184997
 
8.4%
9 147181
 
6.6%
- 128147
 
5.8%
2 113353
 
5.1%
t 105880
 
4.8%
I 89160
 
4.0%
6 79583
 
3.6%
0 76579
 
3.5%
. 65074
 
2.9%
Other values (82) 1007365
45.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2215378
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 218059
 
9.8%
184997
 
8.4%
9 147181
 
6.6%
- 128147
 
5.8%
2 113353
 
5.1%
t 105880
 
4.8%
I 89160
 
4.0%
6 79583
 
3.6%
0 76579
 
3.5%
. 65074
 
2.9%
Other values (82) 1007365
45.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2215378
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 218059
 
9.8%
184997
 
8.4%
9 147181
 
6.6%
- 128147
 
5.8%
2 113353
 
5.1%
t 105880
 
4.8%
I 89160
 
4.0%
6 79583
 
3.6%
0 76579
 
3.5%
. 65074
 
2.9%
Other values (82) 1007365
45.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2215378
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 218059
 
9.8%
184997
 
8.4%
9 147181
 
6.6%
- 128147
 
5.8%
2 113353
 
5.1%
t 105880
 
4.8%
I 89160
 
4.0%
6 79583
 
3.6%
0 76579
 
3.5%
. 65074
 
2.9%
Other values (82) 1007365
45.5%

habitat
Text

Missing 

Distinct89
Distinct (%)44.7%
Missing606573
Missing (%)> 99.9%
Memory size4.6 MiB
2025-03-26T16:20:27.246910image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length103
Median length43
Mean length19.30653266
Min length5

Characters and Unicode

Total characters3842
Distinct characters62
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)32.2%

Sample

1st rowRoadside in coniferous forest
2nd rowOn a figleaf gourd
3rd rowcultivated garden
4th rowhammocks-dense hardwood & Palmetto forests
5th rowvisiting mango flowers
ValueCountFrequency (%)
garden 45
 
7.4%
cultivated 44
 
7.3%
stream 26
 
4.3%
on 26
 
4.3%
forest 23
 
3.8%
in 19
 
3.1%
of 13
 
2.1%
collected 12
 
2.0%
at 9
 
1.5%
terre 8
 
1.3%
Other values (183) 381
62.9%
2025-03-26T16:20:27.370296image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
407
 
10.6%
e 388
 
10.1%
a 308
 
8.0%
r 258
 
6.7%
t 250
 
6.5%
d 224
 
5.8%
n 223
 
5.8%
o 217
 
5.6%
i 190
 
4.9%
l 185
 
4.8%
Other values (52) 1192
31.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3842
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
407
 
10.6%
e 388
 
10.1%
a 308
 
8.0%
r 258
 
6.7%
t 250
 
6.5%
d 224
 
5.8%
n 223
 
5.8%
o 217
 
5.6%
i 190
 
4.9%
l 185
 
4.8%
Other values (52) 1192
31.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3842
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
407
 
10.6%
e 388
 
10.1%
a 308
 
8.0%
r 258
 
6.7%
t 250
 
6.5%
d 224
 
5.8%
n 223
 
5.8%
o 217
 
5.6%
i 190
 
4.9%
l 185
 
4.8%
Other values (52) 1192
31.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3842
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
407
 
10.6%
e 388
 
10.1%
a 308
 
8.0%
r 258
 
6.7%
t 250
 
6.5%
d 224
 
5.8%
n 223
 
5.8%
o 217
 
5.6%
i 190
 
4.9%
l 185
 
4.8%
Other values (52) 1192
31.0%

locationID
Text

Missing 

Distinct186
Distinct (%)17.7%
Missing605724
Missing (%)99.8%
Memory size4.6 MiB
2025-03-26T16:20:27.402812image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length40
Median length14
Mean length10.77862595
Min length1

Characters and Unicode

Total characters11296
Distinct characters56
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)9.1%

Sample

1st rowMEI Site 97-81
2nd rowRD-044
3rd rowMEI Site 97-81
4th rowMEI Site 97-81
5th rowMEI Site 97-81
ValueCountFrequency (%)
mei 653
27.5%
site 611
25.7%
97-81 302
12.7%
97-92 132
 
5.6%
97-90 52
 
2.2%
97-58 46
 
1.9%
97-74 31
 
1.3%
97-88 26
 
1.1%
97-93 24
 
1.0%
k-m1 19
 
0.8%
Other values (196) 481
20.2%
2025-03-26T16:20:27.501720image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1329
 
11.8%
- 988
 
8.7%
9 905
 
8.0%
7 771
 
6.8%
M 699
 
6.2%
I 660
 
5.8%
E 657
 
5.8%
t 639
 
5.7%
e 638
 
5.6%
i 625
 
5.5%
Other values (46) 3385
30.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11296
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1329
 
11.8%
- 988
 
8.7%
9 905
 
8.0%
7 771
 
6.8%
M 699
 
6.2%
I 660
 
5.8%
E 657
 
5.8%
t 639
 
5.7%
e 638
 
5.6%
i 625
 
5.5%
Other values (46) 3385
30.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11296
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1329
 
11.8%
- 988
 
8.7%
9 905
 
8.0%
7 771
 
6.8%
M 699
 
6.2%
I 660
 
5.8%
E 657
 
5.8%
t 639
 
5.7%
e 638
 
5.6%
i 625
 
5.5%
Other values (46) 3385
30.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11296
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1329
 
11.8%
- 988
 
8.7%
9 905
 
8.0%
7 771
 
6.8%
M 699
 
6.2%
I 660
 
5.8%
E 657
 
5.8%
t 639
 
5.7%
e 638
 
5.6%
i 625
 
5.5%
Other values (46) 3385
30.0%

higherGeography
Text

Missing 

Distinct10605
Distinct (%)2.4%
Missing156606
Missing (%)25.8%
Memory size4.6 MiB
2025-03-26T16:20:27.631478image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length101
Median length91
Mean length30.38974956
Min length4

Characters and Unicode

Total characters13680432
Distinct characters132
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3145 ?
Unique (%)0.7%

Sample

1st rowUnited States, [Not Stated], [Not Stated]
2nd rowCosta Rica, Cartago, [Not Stated]
3rd rowUnited States, Alaska, Aleutians West
4th rowUnited States, Virginia, Virginia Beach
5th rowUnited States, New York, [Not Stated]
ValueCountFrequency (%)
united 223614
 
12.1%
states 221878
 
12.1%
not 168606
 
9.2%
stated 168604
 
9.2%
california 23486
 
1.3%
virginia 23402
 
1.3%
new 22582
 
1.2%
colorado 21144
 
1.1%
mexico 21067
 
1.1%
canada 16283
 
0.9%
Other values (6804) 930421
50.5%
2025-03-26T16:20:27.844586image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 1391656
 
10.2%
a 1391612
 
10.2%
1390921
 
10.2%
e 1094737
 
8.0%
i 818896
 
6.0%
n 817030
 
6.0%
, 801681
 
5.9%
o 694950
 
5.1%
d 582456
 
4.3%
s 503425
 
3.7%
Other values (122) 4193068
30.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 13680432
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 1391656
 
10.2%
a 1391612
 
10.2%
1390921
 
10.2%
e 1094737
 
8.0%
i 818896
 
6.0%
n 817030
 
6.0%
, 801681
 
5.9%
o 694950
 
5.1%
d 582456
 
4.3%
s 503425
 
3.7%
Other values (122) 4193068
30.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 13680432
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 1391656
 
10.2%
a 1391612
 
10.2%
1390921
 
10.2%
e 1094737
 
8.0%
i 818896
 
6.0%
n 817030
 
6.0%
, 801681
 
5.9%
o 694950
 
5.1%
d 582456
 
4.3%
s 503425
 
3.7%
Other values (122) 4193068
30.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 13680432
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 1391656
 
10.2%
a 1391612
 
10.2%
1390921
 
10.2%
e 1094737
 
8.0%
i 818896
 
6.0%
n 817030
 
6.0%
, 801681
 
5.9%
o 694950
 
5.1%
d 582456
 
4.3%
s 503425
 
3.7%
Other values (122) 4193068
30.7%

continent
Text

Missing 

Distinct6
Distinct (%)4.7%
Missing606644
Missing (%)> 99.9%
Memory size4.6 MiB
2025-03-26T16:20:27.883602image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length4
Mean length7.15625
Min length4

Characters and Unicode

Total characters916
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.8%

Sample

1st rowSouth America
2nd rowAsia
3rd rowSouth America
4th rowEurope
5th rowAsia
ValueCountFrequency (%)
asia 69
40.8%
america 40
23.7%
north 21
 
12.4%
south 19
 
11.2%
europe 9
 
5.3%
africa 9
 
5.3%
not 1
 
0.6%
stated 1
 
0.6%
2025-03-26T16:20:27.961427image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 119
13.0%
A 118
12.9%
i 118
12.9%
r 79
8.6%
s 69
 
7.5%
o 50
 
5.5%
e 50
 
5.5%
c 49
 
5.3%
t 43
 
4.7%
41
 
4.5%
Other values (11) 180
19.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 916
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 119
13.0%
A 118
12.9%
i 118
12.9%
r 79
8.6%
s 69
 
7.5%
o 50
 
5.5%
e 50
 
5.5%
c 49
 
5.3%
t 43
 
4.7%
41
 
4.5%
Other values (11) 180
19.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 916
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 119
13.0%
A 118
12.9%
i 118
12.9%
r 79
8.6%
s 69
 
7.5%
o 50
 
5.5%
e 50
 
5.5%
c 49
 
5.3%
t 43
 
4.7%
41
 
4.5%
Other values (11) 180
19.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 916
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 119
13.0%
A 118
12.9%
i 118
12.9%
r 79
8.6%
s 69
 
7.5%
o 50
 
5.5%
e 50
 
5.5%
c 49
 
5.3%
t 43
 
4.7%
41
 
4.5%
Other values (11) 180
19.7%

islandGroup
Text

Missing 

Distinct72
Distinct (%)2.8%
Missing604245
Missing (%)99.6%
Memory size4.6 MiB
2025-03-26T16:20:27.992462image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length22
Median length13
Mean length13.71982588
Min length5

Characters and Unicode

Total characters34670
Distinct characters49
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)0.8%

Sample

1st rowSunda Islands
2nd rowInner Islands
3rd rowViti Levu Group
4th rowChuuk Lagoon
5th rowSunda Islands
ValueCountFrequency (%)
islands 2165
42.1%
sunda 958
18.6%
marquesas 249
 
4.8%
solomon 226
 
4.4%
bass 171
 
3.3%
chuuk 150
 
2.9%
lagoon 150
 
2.9%
outer 150
 
2.9%
inner 141
 
2.7%
group 101
 
2.0%
Other values (78) 676
 
13.2%
2025-03-26T16:20:28.088473image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 5375
15.5%
a 4404
12.7%
n 3959
11.4%
d 3275
9.4%
2610
7.5%
l 2573
7.4%
I 2319
6.7%
u 1960
 
5.7%
S 1252
 
3.6%
o 1229
 
3.5%
Other values (39) 5714
16.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 34670
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 5375
15.5%
a 4404
12.7%
n 3959
11.4%
d 3275
9.4%
2610
7.5%
l 2573
7.4%
I 2319
6.7%
u 1960
 
5.7%
S 1252
 
3.6%
o 1229
 
3.5%
Other values (39) 5714
16.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 34670
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 5375
15.5%
a 4404
12.7%
n 3959
11.4%
d 3275
9.4%
2610
7.5%
l 2573
7.4%
I 2319
6.7%
u 1960
 
5.7%
S 1252
 
3.6%
o 1229
 
3.5%
Other values (39) 5714
16.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 34670
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 5375
15.5%
a 4404
12.7%
n 3959
11.4%
d 3275
9.4%
2610
7.5%
l 2573
7.4%
I 2319
6.7%
u 1960
 
5.7%
S 1252
 
3.6%
o 1229
 
3.5%
Other values (39) 5714
16.5%

island
Text

Missing 

Distinct438
Distinct (%)4.7%
Missing597364
Missing (%)98.4%
Memory size4.6 MiB
2025-03-26T16:20:28.213909image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length21
Mean length9.324085884
Min length3

Characters and Unicode

Total characters87721
Distinct characters62
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique170 ?
Unique (%)1.8%

Sample

1st rowSouth Island
2nd rowPohnpei
3rd rowSouth Island
4th rowOahu
5th rowGuadalcanal
ValueCountFrequency (%)
island 3180
21.5%
south 1645
 
11.1%
java 885
 
6.0%
levu 567
 
3.8%
viti 543
 
3.7%
north 519
 
3.5%
guadalcanal 329
 
2.2%
borneo 253
 
1.7%
key 247
 
1.7%
hiva 247
 
1.7%
Other values (440) 6401
43.2%
2025-03-26T16:20:28.405561image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 12991
14.8%
n 6169
 
7.0%
l 5511
 
6.3%
o 5475
 
6.2%
5408
 
6.2%
u 4486
 
5.1%
d 4473
 
5.1%
s 4144
 
4.7%
e 3922
 
4.5%
t 3762
 
4.3%
Other values (52) 31380
35.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 87721
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 12991
14.8%
n 6169
 
7.0%
l 5511
 
6.3%
o 5475
 
6.2%
5408
 
6.2%
u 4486
 
5.1%
d 4473
 
5.1%
s 4144
 
4.7%
e 3922
 
4.5%
t 3762
 
4.3%
Other values (52) 31380
35.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 87721
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 12991
14.8%
n 6169
 
7.0%
l 5511
 
6.3%
o 5475
 
6.2%
5408
 
6.2%
u 4486
 
5.1%
d 4473
 
5.1%
s 4144
 
4.7%
e 3922
 
4.5%
t 3762
 
4.3%
Other values (52) 31380
35.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 87721
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 12991
14.8%
n 6169
 
7.0%
l 5511
 
6.3%
o 5475
 
6.2%
5408
 
6.2%
u 4486
 
5.1%
d 4473
 
5.1%
s 4144
 
4.7%
e 3922
 
4.5%
t 3762
 
4.3%
Other values (52) 31380
35.8%

country
Text

Missing 

Distinct362
Distinct (%)0.1%
Missing156628
Missing (%)25.8%
Memory size4.6 MiB
2025-03-26T16:20:28.538254image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length57
Median length44
Mean length10.35687691
Min length4

Characters and Unicode

Total characters4662086
Distinct characters66
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)< 0.1%

Sample

1st rowUnited States
2nd rowCosta Rica
3rd rowUnited States
4th rowUnited States
5th rowUnited States
ValueCountFrequency (%)
united 223394
30.9%
states 221660
30.7%
canada 16282
 
2.3%
mexico 15859
 
2.2%
china 14584
 
2.0%
brazil 13021
 
1.8%
costa 8942
 
1.2%
rica 8942
 
1.2%
peru 7655
 
1.1%
india 7052
 
1.0%
Other values (377) 185328
25.6%
2025-03-26T16:20:28.733579image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 720732
15.5%
e 562691
12.1%
a 530379
11.4%
i 391083
8.4%
n 366641
7.9%
d 288367
 
6.2%
272575
 
5.8%
s 262014
 
5.6%
S 245094
 
5.3%
U 224703
 
4.8%
Other values (56) 797807
17.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4662086
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 720732
15.5%
e 562691
12.1%
a 530379
11.4%
i 391083
8.4%
n 366641
7.9%
d 288367
 
6.2%
272575
 
5.8%
s 262014
 
5.6%
S 245094
 
5.3%
U 224703
 
4.8%
Other values (56) 797807
17.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4662086
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 720732
15.5%
e 562691
12.1%
a 530379
11.4%
i 391083
8.4%
n 366641
7.9%
d 288367
 
6.2%
272575
 
5.8%
s 262014
 
5.6%
S 245094
 
5.3%
U 224703
 
4.8%
Other values (56) 797807
17.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4662086
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 720732
15.5%
e 562691
12.1%
a 530379
11.4%
i 391083
8.4%
n 366641
7.9%
d 288367
 
6.2%
272575
 
5.8%
s 262014
 
5.6%
S 245094
 
5.3%
U 224703
 
4.8%
Other values (56) 797807
17.1%

stateProvince
Text

Missing 

Distinct3071
Distinct (%)0.7%
Missing173815
Missing (%)28.6%
Memory size4.6 MiB
2025-03-26T16:20:28.871531image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length57
Median length44
Mean length9.044678802
Min length2

Characters and Unicode

Total characters3915957
Distinct characters117
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique809 ?
Unique (%)0.2%

Sample

1st row[Not Stated]
2nd rowCartago
3rd rowAlaska
4th rowVirginia
5th rowNew York
ValueCountFrequency (%)
not 29540
 
5.2%
stated 29540
 
5.2%
california 23397
 
4.1%
virginia 22089
 
3.9%
colorado 21015
 
3.7%
new 16704
 
2.9%
texas 12372
 
2.2%
arizona 12175
 
2.1%
florida 9931
 
1.7%
maryland 9654
 
1.7%
Other values (2918) 381160
67.2%
2025-03-26T16:20:29.081083image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 526102
 
13.4%
o 334312
 
8.5%
i 322878
 
8.2%
n 300116
 
7.7%
r 250945
 
6.4%
e 217420
 
5.6%
t 209356
 
5.3%
s 152436
 
3.9%
l 138772
 
3.5%
134620
 
3.4%
Other values (107) 1329000
33.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3915957
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 526102
 
13.4%
o 334312
 
8.5%
i 322878
 
8.2%
n 300116
 
7.7%
r 250945
 
6.4%
e 217420
 
5.6%
t 209356
 
5.3%
s 152436
 
3.9%
l 138772
 
3.5%
134620
 
3.4%
Other values (107) 1329000
33.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3915957
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 526102
 
13.4%
o 334312
 
8.5%
i 322878
 
8.2%
n 300116
 
7.7%
r 250945
 
6.4%
e 217420
 
5.6%
t 209356
 
5.3%
s 152436
 
3.9%
l 138772
 
3.5%
134620
 
3.4%
Other values (107) 1329000
33.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3915957
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 526102
 
13.4%
o 334312
 
8.5%
i 322878
 
8.2%
n 300116
 
7.7%
r 250945
 
6.4%
e 217420
 
5.6%
t 209356
 
5.3%
s 152436
 
3.9%
l 138772
 
3.5%
134620
 
3.4%
Other values (107) 1329000
33.9%

county
Text

Missing 

Distinct4070
Distinct (%)1.2%
Missing255726
Missing (%)42.1%
Memory size4.6 MiB
2025-03-26T16:20:29.224759image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length51
Median length45
Mean length9.456840414
Min length1

Characters and Unicode

Total characters3319786
Distinct characters98
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1156 ?
Unique (%)0.3%

Sample

1st row[Not Stated]
2nd row[Not Stated]
3rd rowAleutians West
4th rowVirginia Beach
5th row[Not Stated]
ValueCountFrequency (%)
not 132529
25.3%
stated 132527
25.3%
boulder 6810
 
1.3%
creek 6780
 
1.3%
clear 6771
 
1.3%
san 5425
 
1.0%
montgomery 4957
 
0.9%
cochise 4332
 
0.8%
prince 3512
 
0.7%
tuolumne 3210
 
0.6%
Other values (4081) 216029
41.3%
2025-03-26T16:20:29.431824image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 457092
13.8%
a 310951
 
9.4%
e 306786
 
9.2%
o 265653
 
8.0%
171836
 
5.2%
d 169817
 
5.1%
S 152672
 
4.6%
N 138177
 
4.2%
n 134293
 
4.0%
[ 132547
 
4.0%
Other values (88) 1079962
32.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3319786
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 457092
13.8%
a 310951
 
9.4%
e 306786
 
9.2%
o 265653
 
8.0%
171836
 
5.2%
d 169817
 
5.1%
S 152672
 
4.6%
N 138177
 
4.2%
n 134293
 
4.0%
[ 132547
 
4.0%
Other values (88) 1079962
32.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3319786
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 457092
13.8%
a 310951
 
9.4%
e 306786
 
9.2%
o 265653
 
8.0%
171836
 
5.2%
d 169817
 
5.1%
S 152672
 
4.6%
N 138177
 
4.2%
n 134293
 
4.0%
[ 132547
 
4.0%
Other values (88) 1079962
32.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3319786
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 457092
13.8%
a 310951
 
9.4%
e 306786
 
9.2%
o 265653
 
8.0%
171836
 
5.2%
d 169817
 
5.1%
S 152672
 
4.6%
N 138177
 
4.2%
n 134293
 
4.0%
[ 132547
 
4.0%
Other values (88) 1079962
32.5%

locality
Text

Missing 

Distinct76770
Distinct (%)17.1%
Missing158877
Missing (%)26.2%
Memory size4.6 MiB
2025-03-26T16:20:29.586636image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length212
Median length175
Mean length21.69028455
Min length1

Characters and Unicode

Total characters9714970
Distinct characters143
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44546 ?
Unique (%)9.9%

Sample

1st row[Not Stated]
2nd rowRio Aquiares, Turrialba
3rd rowSaint Paul Island, Bering Sea
4th rowFalse Cape State Park, Wash Woods, 100 meters east of Interpreter's residence
5th row[Not Stated]
ValueCountFrequency (%)
not 65578
 
4.3%
stated 65502
 
4.3%
of 41953
 
2.7%
miles 21253
 
1.4%
kilometers 15809
 
1.0%
park 15494
 
1.0%
river 15392
 
1.0%
lake 14868
 
1.0%
near 12868
 
0.8%
creek 12667
 
0.8%
Other values (46996) 1255074
81.7%
2025-03-26T16:20:29.806048image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1088563
 
11.2%
a 919277
 
9.5%
e 739653
 
7.6%
o 644162
 
6.6%
t 608662
 
6.3%
n 493220
 
5.1%
i 469217
 
4.8%
r 467592
 
4.8%
l 375868
 
3.9%
s 349513
 
3.6%
Other values (133) 3559243
36.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9714970
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1088563
 
11.2%
a 919277
 
9.5%
e 739653
 
7.6%
o 644162
 
6.6%
t 608662
 
6.3%
n 493220
 
5.1%
i 469217
 
4.8%
r 467592
 
4.8%
l 375868
 
3.9%
s 349513
 
3.6%
Other values (133) 3559243
36.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9714970
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1088563
 
11.2%
a 919277
 
9.5%
e 739653
 
7.6%
o 644162
 
6.6%
t 608662
 
6.3%
n 493220
 
5.1%
i 469217
 
4.8%
r 467592
 
4.8%
l 375868
 
3.9%
s 349513
 
3.6%
Other values (133) 3559243
36.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9714970
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1088563
 
11.2%
a 919277
 
9.5%
e 739653
 
7.6%
o 644162
 
6.6%
t 608662
 
6.3%
n 493220
 
5.1%
i 469217
 
4.8%
r 467592
 
4.8%
l 375868
 
3.9%
s 349513
 
3.6%
Other values (133) 3559243
36.6%
Distinct1814
Distinct (%)3.9%
Missing559942
Missing (%)92.3%
Memory size4.6 MiB
2025-03-26T16:20:29.942321image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.369933803
Min length3

Characters and Unicode

Total characters251474
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique455 ?
Unique (%)1.0%

Sample

1st row2040.0
2nd row240.0
3rd row165.0
4th row400.0
5th row1300.0
ValueCountFrequency (%)
2743.0 1189
 
2.5%
3353.0 911
 
1.9%
1829.0 816
 
1.7%
610.0 656
 
1.4%
1524.0 630
 
1.3%
914.0 613
 
1.3%
427.0 569
 
1.2%
1100.0 566
 
1.2%
200.0 532
 
1.1%
1372.0 525
 
1.1%
Other values (1800) 39823
85.0%
2025-03-26T16:20:30.140238image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 76223
30.3%
. 46830
18.6%
1 25491
 
10.1%
2 21243
 
8.4%
3 15807
 
6.3%
5 14115
 
5.6%
4 13741
 
5.5%
7 11277
 
4.5%
9 9396
 
3.7%
6 9386
 
3.7%
Other values (2) 7965
 
3.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 251474
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 76223
30.3%
. 46830
18.6%
1 25491
 
10.1%
2 21243
 
8.4%
3 15807
 
6.3%
5 14115
 
5.6%
4 13741
 
5.5%
7 11277
 
4.5%
9 9396
 
3.7%
6 9386
 
3.7%
Other values (2) 7965
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 251474
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 76223
30.3%
. 46830
18.6%
1 25491
 
10.1%
2 21243
 
8.4%
3 15807
 
6.3%
5 14115
 
5.6%
4 13741
 
5.5%
7 11277
 
4.5%
9 9396
 
3.7%
6 9386
 
3.7%
Other values (2) 7965
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 251474
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 76223
30.3%
. 46830
18.6%
1 25491
 
10.1%
2 21243
 
8.4%
3 15807
 
6.3%
5 14115
 
5.6%
4 13741
 
5.5%
7 11277
 
4.5%
9 9396
 
3.7%
6 9386
 
3.7%
Other values (2) 7965
 
3.2%
Distinct1535
Distinct (%)4.9%
Missing575208
Missing (%)94.8%
Memory size4.6 MiB
2025-03-26T16:20:30.280666image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.47294386
Min length3

Characters and Unicode

Total characters172748
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique402 ?
Unique (%)1.3%

Sample

1st row2040.0
2nd row240.0
3rd row165.0
4th row400.0
5th row1300.0
ValueCountFrequency (%)
3353.0 852
 
2.7%
2438.0 723
 
2.3%
1829.0 720
 
2.3%
1524.0 586
 
1.9%
2743.0 556
 
1.8%
427.0 468
 
1.5%
1200.0 465
 
1.5%
1372.0 459
 
1.5%
2134.0 424
 
1.3%
2499.0 418
 
1.3%
Other values (1524) 25893
82.0%
2025-03-26T16:20:30.487819image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 51925
30.1%
. 31564
18.3%
1 16855
 
9.8%
2 15404
 
8.9%
3 10922
 
6.3%
4 9752
 
5.6%
5 9589
 
5.6%
7 8024
 
4.6%
9 6280
 
3.6%
8 6260
 
3.6%
Other values (2) 6173
 
3.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 172748
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 51925
30.1%
. 31564
18.3%
1 16855
 
9.8%
2 15404
 
8.9%
3 10922
 
6.3%
4 9752
 
5.6%
5 9589
 
5.6%
7 8024
 
4.6%
9 6280
 
3.6%
8 6260
 
3.6%
Other values (2) 6173
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 172748
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 51925
30.1%
. 31564
18.3%
1 16855
 
9.8%
2 15404
 
8.9%
3 10922
 
6.3%
4 9752
 
5.6%
5 9589
 
5.6%
7 8024
 
4.6%
9 6280
 
3.6%
8 6260
 
3.6%
Other values (2) 6173
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 172748
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 51925
30.1%
. 31564
18.3%
1 16855
 
9.8%
2 15404
 
8.9%
3 10922
 
6.3%
4 9752
 
5.6%
5 9589
 
5.6%
7 8024
 
4.6%
9 6280
 
3.6%
8 6260
 
3.6%
Other values (2) 6173
 
3.6%

verbatimElevation
Text

Missing 

Distinct1025
Distinct (%)10.3%
Missing596798
Missing (%)98.4%
Memory size4.6 MiB
2025-03-26T16:20:30.630615image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length94
Median length31
Mean length8.083918187
Min length1

Characters and Unicode

Total characters80629
Distinct characters54
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique335 ?
Unique (%)3.4%

Sample

1st row140 meters
2nd row3900 feet
3rd row5940 feet
4th row180 meters
5th row3000 feet
ValueCountFrequency (%)
m 2794
 
14.5%
feet 2481
 
12.9%
meters 1522
 
7.9%
ft 1472
 
7.6%
1000 348
 
1.8%
level 319
 
1.7%
sea 319
 
1.7%
300 306
 
1.6%
near 277
 
1.4%
3200 238
 
1.2%
Other values (620) 9228
47.8%
2025-03-26T16:20:30.822847image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 16948
21.0%
e 9382
11.6%
9330
11.6%
t 5757
 
7.1%
m 5123
 
6.4%
f 4120
 
5.1%
1 4108
 
5.1%
5 3803
 
4.7%
2 2921
 
3.6%
. 2471
 
3.1%
Other values (44) 16666
20.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 80629
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 16948
21.0%
e 9382
11.6%
9330
11.6%
t 5757
 
7.1%
m 5123
 
6.4%
f 4120
 
5.1%
1 4108
 
5.1%
5 3803
 
4.7%
2 2921
 
3.6%
. 2471
 
3.1%
Other values (44) 16666
20.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 80629
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 16948
21.0%
e 9382
11.6%
9330
11.6%
t 5757
 
7.1%
m 5123
 
6.4%
f 4120
 
5.1%
1 4108
 
5.1%
5 3803
 
4.7%
2 2921
 
3.6%
. 2471
 
3.1%
Other values (44) 16666
20.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 80629
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 16948
21.0%
e 9382
11.6%
9330
11.6%
t 5757
 
7.1%
m 5123
 
6.4%
f 4120
 
5.1%
1 4108
 
5.1%
5 3803
 
4.7%
2 2921
 
3.6%
. 2471
 
3.1%
Other values (44) 16666
20.7%

minimumDepthInMeters
Text

Missing 

Distinct12
Distinct (%)35.3%
Missing606738
Missing (%)> 99.9%
Memory size4.6 MiB
2025-03-26T16:20:30.866380image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.794117647
Min length3

Characters and Unicode

Total characters163
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)17.6%

Sample

1st row0.0
2nd row250.0
3rd row0.0
4th row370.0
5th row359.0
ValueCountFrequency (%)
250.0 9
26.5%
0.0 6
17.6%
880.0 6
17.6%
370.0 3
 
8.8%
1707.0 2
 
5.9%
775.0 2
 
5.9%
359.0 1
 
2.9%
1400.0 1
 
2.9%
1743.0 1
 
2.9%
500.0 1
 
2.9%
Other values (2) 2
 
5.9%
2025-03-26T16:20:30.955840image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 68
41.7%
. 34
20.9%
5 13
 
8.0%
7 13
 
8.0%
8 12
 
7.4%
2 9
 
5.5%
3 6
 
3.7%
1 4
 
2.5%
4 2
 
1.2%
9 1
 
0.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 163
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 68
41.7%
. 34
20.9%
5 13
 
8.0%
7 13
 
8.0%
8 12
 
7.4%
2 9
 
5.5%
3 6
 
3.7%
1 4
 
2.5%
4 2
 
1.2%
9 1
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 163
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 68
41.7%
. 34
20.9%
5 13
 
8.0%
7 13
 
8.0%
8 12
 
7.4%
2 9
 
5.5%
3 6
 
3.7%
1 4
 
2.5%
4 2
 
1.2%
9 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 163
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 68
41.7%
. 34
20.9%
5 13
 
8.0%
7 13
 
8.0%
8 12
 
7.4%
2 9
 
5.5%
3 6
 
3.7%
1 4
 
2.5%
4 2
 
1.2%
9 1
 
0.6%

maximumDepthInMeters
Text

Missing 

Distinct4
Distinct (%)36.4%
Missing606761
Missing (%)> 99.9%
Memory size4.6 MiB
2025-03-26T16:20:30.986365image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5.090909091
Min length5

Characters and Unicode

Total characters56
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)18.2%

Sample

1st row220.0
2nd row220.0
3rd row370.0
4th row220.0
5th row1400.0
ValueCountFrequency (%)
220.0 6
54.5%
370.0 3
27.3%
1400.0 1
 
9.1%
500.0 1
 
9.1%
2025-03-26T16:20:31.068496image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 24
42.9%
2 12
21.4%
. 11
19.6%
3 3
 
5.4%
7 3
 
5.4%
1 1
 
1.8%
4 1
 
1.8%
5 1
 
1.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 56
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 24
42.9%
2 12
21.4%
. 11
19.6%
3 3
 
5.4%
7 3
 
5.4%
1 1
 
1.8%
4 1
 
1.8%
5 1
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 56
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 24
42.9%
2 12
21.4%
. 11
19.6%
3 3
 
5.4%
7 3
 
5.4%
1 1
 
1.8%
4 1
 
1.8%
5 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 56
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 24
42.9%
2 12
21.4%
. 11
19.6%
3 3
 
5.4%
7 3
 
5.4%
1 1
 
1.8%
4 1
 
1.8%
5 1
 
1.8%

verbatimDepth
Text

Constant  Missing 

Distinct1
Distinct (%)16.7%
Missing606766
Missing (%)> 99.9%
Memory size4.6 MiB
2025-03-26T16:20:31.096561image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters150
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row220m inside cave entrance
2nd row220m inside cave entrance
3rd row220m inside cave entrance
4th row220m inside cave entrance
5th row220m inside cave entrance
ValueCountFrequency (%)
220m 6
25.0%
inside 6
25.0%
cave 6
25.0%
entrance 6
25.0%
2025-03-26T16:20:31.174284image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 24
16.0%
18
12.0%
n 18
12.0%
2 12
8.0%
i 12
8.0%
c 12
8.0%
a 12
8.0%
0 6
 
4.0%
m 6
 
4.0%
s 6
 
4.0%
Other values (4) 24
16.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 150
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 24
16.0%
18
12.0%
n 18
12.0%
2 12
8.0%
i 12
8.0%
c 12
8.0%
a 12
8.0%
0 6
 
4.0%
m 6
 
4.0%
s 6
 
4.0%
Other values (4) 24
16.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 150
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 24
16.0%
18
12.0%
n 18
12.0%
2 12
8.0%
i 12
8.0%
c 12
8.0%
a 12
8.0%
0 6
 
4.0%
m 6
 
4.0%
s 6
 
4.0%
Other values (4) 24
16.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 150
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 24
16.0%
18
12.0%
n 18
12.0%
2 12
8.0%
i 12
8.0%
c 12
8.0%
a 12
8.0%
0 6
 
4.0%
m 6
 
4.0%
s 6
 
4.0%
Other values (4) 24
16.0%

decimalLatitude
Text

Missing 

Distinct38064
Distinct (%)11.9%
Missing286669
Missing (%)47.2%
Memory size4.6 MiB
2025-03-26T16:20:31.309309image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length7
Mean length6.689831086
Min length3

Characters and Unicode

Total characters2141435
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15813 ?
Unique (%)4.9%

Sample

1st row9.91378
2nd row57.18
3rd row36.5787
4th row15.5864
5th row45.4838
ValueCountFrequency (%)
39.6891 5068
 
1.6%
60.75 3856
 
1.2%
60.7493 2469
 
0.8%
40.0925 2386
 
0.7%
38.02 2015
 
0.6%
42.7299 1704
 
0.5%
37.23 1349
 
0.4%
40.015 1289
 
0.4%
42.78 1177
 
0.4%
38.9559 1146
 
0.4%
Other values (37372) 297644
93.0%
2025-03-26T16:20:31.513692image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 320103
14.9%
3 274701
12.8%
4 209875
9.8%
1 189587
8.9%
2 172940
8.1%
9 170192
7.9%
7 166164
7.8%
8 159546
7.5%
5 153745
7.2%
6 152876
7.1%
Other values (3) 171706
8.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2141435
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 320103
14.9%
3 274701
12.8%
4 209875
9.8%
1 189587
8.9%
2 172940
8.1%
9 170192
7.9%
7 166164
7.8%
8 159546
7.5%
5 153745
7.2%
6 152876
7.1%
Other values (3) 171706
8.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2141435
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 320103
14.9%
3 274701
12.8%
4 209875
9.8%
1 189587
8.9%
2 172940
8.1%
9 170192
7.9%
7 166164
7.8%
8 159546
7.5%
5 153745
7.2%
6 152876
7.1%
Other values (3) 171706
8.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2141435
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 320103
14.9%
3 274701
12.8%
4 209875
9.8%
1 189587
8.9%
2 172940
8.1%
9 170192
7.9%
7 166164
7.8%
8 159546
7.5%
5 153745
7.2%
6 152876
7.1%
Other values (3) 171706
8.0%

decimalLongitude
Text

Missing 

Distinct37011
Distinct (%)11.6%
Missing286669
Missing (%)47.2%
Memory size4.6 MiB
2025-03-26T16:20:31.664283image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length8
Mean length7.477465066
Min length3

Characters and Unicode

Total characters2393559
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15092 ?
Unique (%)4.7%

Sample

1st row-83.6744
2nd row-170.27
3rd row-75.8881
4th row-61.4739
5th row-75.9727
ValueCountFrequency (%)
105.644 5118
 
1.6%
139.5 3854
 
1.2%
139.504 2469
 
0.8%
105.358 2386
 
0.7%
87.8123 1704
 
0.5%
119.93 1405
 
0.4%
105.27 1363
 
0.4%
80.4178 1328
 
0.4%
0.365 1305
 
0.4%
87.76 1170
 
0.4%
Other values (36499) 298001
93.1%
2025-03-26T16:20:31.870897image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 320103
13.4%
1 293881
12.3%
- 271666
11.3%
7 218301
9.1%
8 194585
8.1%
6 165988
6.9%
5 163286
6.8%
3 159043
6.6%
2 157375
6.6%
9 154969
6.5%
Other values (2) 294362
12.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2393559
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 320103
13.4%
1 293881
12.3%
- 271666
11.3%
7 218301
9.1%
8 194585
8.1%
6 165988
6.9%
5 163286
6.8%
3 159043
6.6%
2 157375
6.6%
9 154969
6.5%
Other values (2) 294362
12.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2393559
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 320103
13.4%
1 293881
12.3%
- 271666
11.3%
7 218301
9.1%
8 194585
8.1%
6 165988
6.9%
5 163286
6.8%
3 159043
6.6%
2 157375
6.6%
9 154969
6.5%
Other values (2) 294362
12.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2393559
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 320103
13.4%
1 293881
12.3%
- 271666
11.3%
7 218301
9.1%
8 194585
8.1%
6 165988
6.9%
5 163286
6.8%
3 159043
6.6%
2 157375
6.6%
9 154969
6.5%
Other values (2) 294362
12.3%

geodeticDatum
Text

Missing 

Distinct5
Distinct (%)< 0.1%
Missing580298
Missing (%)95.6%
Memory size4.6 MiB
2025-03-26T16:20:32.054374image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length18
Median length18
Mean length17.50185087
Min length5

Characters and Unicode

Total characters463344
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowWGS 84 (EPSG:4326)
2nd rowWGS 84 (EPSG:4326)
3rd rowWGS 84 (EPSG:4326)
4th rowWGS 84 (EPSG:4326)
5th rowWGS 84 (EPSG:4326)
ValueCountFrequency (%)
wgs 25094
32.6%
84 25094
32.6%
epsg:4326 25088
32.6%
wgs84 761
 
1.0%
nad83 402
 
0.5%
epsg:4269 402
 
0.5%
wgs40 217
 
0.3%
2025-03-26T16:20:32.143123image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
S 51562
11.1%
4 51562
11.1%
G 51562
11.1%
50584
10.9%
8 26257
 
5.7%
W 26072
 
5.6%
3 25490
 
5.5%
) 25490
 
5.5%
6 25490
 
5.5%
2 25490
 
5.5%
Other values (9) 103785
22.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 463344
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
S 51562
11.1%
4 51562
11.1%
G 51562
11.1%
50584
10.9%
8 26257
 
5.7%
W 26072
 
5.6%
3 25490
 
5.5%
) 25490
 
5.5%
6 25490
 
5.5%
2 25490
 
5.5%
Other values (9) 103785
22.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 463344
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
S 51562
11.1%
4 51562
11.1%
G 51562
11.1%
50584
10.9%
8 26257
 
5.7%
W 26072
 
5.6%
3 25490
 
5.5%
) 25490
 
5.5%
6 25490
 
5.5%
2 25490
 
5.5%
Other values (9) 103785
22.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 463344
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
S 51562
11.1%
4 51562
11.1%
G 51562
11.1%
50584
10.9%
8 26257
 
5.7%
W 26072
 
5.6%
3 25490
 
5.5%
) 25490
 
5.5%
6 25490
 
5.5%
2 25490
 
5.5%
Other values (9) 103785
22.4%
Distinct1496
Distinct (%)12.5%
Missing594787
Missing (%)98.0%
Memory size4.6 MiB
2025-03-26T16:20:32.268546image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.137922403
Min length2

Characters and Unicode

Total characters49593
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique746 ?
Unique (%)6.2%

Sample

1st row931
2nd row10206
3rd row6642
4th row3036
5th row301
ValueCountFrequency (%)
3036 1749
 
14.6%
301 469
 
3.9%
34239 426
 
3.6%
1189 258
 
2.2%
20000 247
 
2.1%
3048 222
 
1.9%
15000 199
 
1.7%
52150 194
 
1.6%
14563 163
 
1.4%
9346 135
 
1.1%
Other values (1486) 7923
66.1%
2025-03-26T16:20:32.459281image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9264
18.7%
3 8274
16.7%
1 6368
12.8%
2 4907
9.9%
6 4655
9.4%
4 3922
7.9%
5 3510
 
7.1%
9 3070
 
6.2%
8 2871
 
5.8%
7 2752
 
5.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 49593
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 9264
18.7%
3 8274
16.7%
1 6368
12.8%
2 4907
9.9%
6 4655
9.4%
4 3922
7.9%
5 3510
 
7.1%
9 3070
 
6.2%
8 2871
 
5.8%
7 2752
 
5.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 49593
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 9264
18.7%
3 8274
16.7%
1 6368
12.8%
2 4907
9.9%
6 4655
9.4%
4 3922
7.9%
5 3510
 
7.1%
9 3070
 
6.2%
8 2871
 
5.8%
7 2752
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 49593
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 9264
18.7%
3 8274
16.7%
1 6368
12.8%
2 4907
9.9%
6 4655
9.4%
4 3922
7.9%
5 3510
 
7.1%
9 3070
 
6.2%
8 2871
 
5.8%
7 2752
 
5.5%

verbatimLatitude
Text

Missing 

Distinct10304
Distinct (%)12.6%
Missing524830
Missing (%)86.5%
Memory size4.6 MiB
2025-03-26T16:20:32.595145image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length31
Median length9
Mean length8.944241049
Min length2

Characters and Unicode

Total characters732909
Distinct characters54
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3873 ?
Unique (%)4.7%

Sample

1st rowN36.578717
2nd row0 deg 50' 00" N
3rd row3 deg. 21.1' N
4th row10 32' S
5th row39.079276
ValueCountFrequency (%)
n 12251
 
10.3%
deg 3794
 
3.2%
s 3074
 
2.6%
40.014986 1229
 
1.0%
38.955944 1144
 
1.0%
39 895
 
0.8%
10 856
 
0.7%
12 809
 
0.7%
40.001652 793
 
0.7%
38 786
 
0.7%
Other values (9213) 93589
78.5%
2025-03-26T16:20:32.785388image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 80111
10.9%
. 76901
10.5%
4 74780
10.2%
1 56675
 
7.7%
2 53548
 
7.3%
8 52169
 
7.1%
0 49325
 
6.7%
9 48745
 
6.7%
5 48476
 
6.6%
6 41952
 
5.7%
Other values (44) 150227
20.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 732909
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3 80111
10.9%
. 76901
10.5%
4 74780
10.2%
1 56675
 
7.7%
2 53548
 
7.3%
8 52169
 
7.1%
0 49325
 
6.7%
9 48745
 
6.7%
5 48476
 
6.6%
6 41952
 
5.7%
Other values (44) 150227
20.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 732909
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3 80111
10.9%
. 76901
10.5%
4 74780
10.2%
1 56675
 
7.7%
2 53548
 
7.3%
8 52169
 
7.1%
0 49325
 
6.7%
9 48745
 
6.7%
5 48476
 
6.6%
6 41952
 
5.7%
Other values (44) 150227
20.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 732909
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3 80111
10.9%
. 76901
10.5%
4 74780
10.2%
1 56675
 
7.7%
2 53548
 
7.3%
8 52169
 
7.1%
0 49325
 
6.7%
9 48745
 
6.7%
5 48476
 
6.6%
6 41952
 
5.7%
Other values (44) 150227
20.5%

verbatimLongitude
Text

Missing 

Distinct10197
Distinct (%)12.4%
Missing524799
Missing (%)86.5%
Memory size4.6 MiB
2025-03-26T16:20:32.919307image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length31
Median length28
Mean length9.81741549
Min length2

Characters and Unicode

Total characters804763
Distinct characters54
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3803 ?
Unique (%)4.6%

Sample

1st rowW75.88805
2nd row66 deg 09' 44" W
3rd row59 deg. 40.5' W
4th row62 48' W
5th row-76.59802
ValueCountFrequency (%)
w 13085
 
11.0%
deg 3773
 
3.2%
e 2370
 
2.0%
105.270546 1262
 
1.1%
76.94553 1144
 
1.0%
76 1017
 
0.9%
59 841
 
0.7%
105.307491 793
 
0.7%
70 786
 
0.7%
77.254426 778
 
0.7%
Other values (9275) 93060
78.3%
2025-03-26T16:20:33.123910image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 79118
 
9.8%
. 76930
 
9.6%
1 65663
 
8.2%
8 62156
 
7.7%
0 59659
 
7.4%
5 56578
 
7.0%
6 55738
 
6.9%
- 52948
 
6.6%
2 49011
 
6.1%
3 48864
 
6.1%
Other values (44) 198098
24.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 804763
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
7 79118
 
9.8%
. 76930
 
9.6%
1 65663
 
8.2%
8 62156
 
7.7%
0 59659
 
7.4%
5 56578
 
7.0%
6 55738
 
6.9%
- 52948
 
6.6%
2 49011
 
6.1%
3 48864
 
6.1%
Other values (44) 198098
24.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 804763
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
7 79118
 
9.8%
. 76930
 
9.6%
1 65663
 
8.2%
8 62156
 
7.7%
0 59659
 
7.4%
5 56578
 
7.0%
6 55738
 
6.9%
- 52948
 
6.6%
2 49011
 
6.1%
3 48864
 
6.1%
Other values (44) 198098
24.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 804763
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
7 79118
 
9.8%
. 76930
 
9.6%
1 65663
 
8.2%
8 62156
 
7.7%
0 59659
 
7.4%
5 56578
 
7.0%
6 55738
 
6.9%
- 52948
 
6.6%
2 49011
 
6.1%
3 48864
 
6.1%
Other values (44) 198098
24.6%

verbatimCoordinateSystem
Text

Constant  Missing 

Distinct1
Distinct (%)100.0%
Missing606771
Missing (%)> 99.9%
Memory size4.6 MiB
2025-03-26T16:20:33.162079image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters23
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st rowDegrees Minutes Seconds
ValueCountFrequency (%)
degrees 1
33.3%
minutes 1
33.3%
seconds 1
33.3%
2025-03-26T16:20:33.240190image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 5
21.7%
s 3
13.0%
2
 
8.7%
n 2
 
8.7%
D 1
 
4.3%
g 1
 
4.3%
r 1
 
4.3%
M 1
 
4.3%
i 1
 
4.3%
u 1
 
4.3%
Other values (5) 5
21.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 23
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 5
21.7%
s 3
13.0%
2
 
8.7%
n 2
 
8.7%
D 1
 
4.3%
g 1
 
4.3%
r 1
 
4.3%
M 1
 
4.3%
i 1
 
4.3%
u 1
 
4.3%
Other values (5) 5
21.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 23
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 5
21.7%
s 3
13.0%
2
 
8.7%
n 2
 
8.7%
D 1
 
4.3%
g 1
 
4.3%
r 1
 
4.3%
M 1
 
4.3%
i 1
 
4.3%
u 1
 
4.3%
Other values (5) 5
21.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 23
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 5
21.7%
s 3
13.0%
2
 
8.7%
n 2
 
8.7%
D 1
 
4.3%
g 1
 
4.3%
r 1
 
4.3%
M 1
 
4.3%
i 1
 
4.3%
u 1
 
4.3%
Other values (5) 5
21.7%

georeferenceProtocol
Text

Missing 

Distinct64
Distinct (%)< 0.1%
Missing368077
Missing (%)60.7%
Memory size4.6 MiB
2025-03-26T16:20:33.270581image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length72
Median length12
Mean length10.94733865
Min length3

Characters and Unicode

Total characters2613075
Distinct characters61
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)< 0.1%

Sample

1st rowGoogle Maps
2nd rowGoogle Earth
3rd rowGoogle Earth
4th rowGEOLocate
5th rowGoogle Earth
ValueCountFrequency (%)
google 163959
40.4%
earth 121183
29.8%
geolocate 70988
17.5%
maps 42802
 
10.5%
gps 1521
 
0.4%
coordinates 783
 
0.2%
centroid 782
 
0.2%
geonames 720
 
0.2%
from 712
 
0.2%
country 672
 
0.2%
Other values (105) 2062
 
0.5%
2025-03-26T16:20:33.372939image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 403971
15.5%
e 239432
9.2%
a 238297
9.1%
G 237364
9.1%
t 195461
7.5%
E 192075
7.4%
l 170082
 
6.5%
167489
 
6.4%
g 164391
 
6.3%
r 124790
 
4.8%
Other values (51) 479723
18.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2613075
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 403971
15.5%
e 239432
9.2%
a 238297
9.1%
G 237364
9.1%
t 195461
7.5%
E 192075
7.4%
l 170082
 
6.5%
167489
 
6.4%
g 164391
 
6.3%
r 124790
 
4.8%
Other values (51) 479723
18.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2613075
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 403971
15.5%
e 239432
9.2%
a 238297
9.1%
G 237364
9.1%
t 195461
7.5%
E 192075
7.4%
l 170082
 
6.5%
167489
 
6.4%
g 164391
 
6.3%
r 124790
 
4.8%
Other values (51) 479723
18.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2613075
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 403971
15.5%
e 239432
9.2%
a 238297
9.1%
G 237364
9.1%
t 195461
7.5%
E 192075
7.4%
l 170082
 
6.5%
167489
 
6.4%
g 164391
 
6.3%
r 124790
 
4.8%
Other values (51) 479723
18.4%

georeferenceRemarks
Text

Missing 

Distinct1135
Distinct (%)13.4%
Missing598295
Missing (%)98.6%
Memory size4.6 MiB
2025-03-26T16:20:33.495841image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length200
Median length182
Mean length45.16704023
Min length10

Characters and Unicode

Total characters382881
Distinct characters69
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique400 ?
Unique (%)4.7%

Sample

1st rowCoordinate Uncertainty In Meters: 56182
2nd rowCoordinate Uncertainty In Meters: 49611
3rd rowCoordinate Uncertainty In Meters: 97700
4th rowCoordinate Uncertainty In Meters: 41787
5th rowCoordinate Uncertainty In Meters: 71236
ValueCountFrequency (%)
in 8306
17.4%
coordinate 8167
17.1%
meters 8167
17.1%
uncertainty 8167
17.1%
verbatim 1310
 
2.7%
coordinate-degrees 1310
 
2.7%
minutes 1310
 
2.7%
3792 274
 
0.6%
the 223
 
0.5%
6066 174
 
0.4%
Other values (1274) 10460
21.9%
2025-03-26T16:20:33.692649image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 42406
 
11.1%
39391
 
10.3%
t 37639
 
9.8%
n 36282
 
9.5%
r 29477
 
7.7%
i 21411
 
5.6%
o 20202
 
5.3%
a 20053
 
5.2%
s 11795
 
3.1%
d 9781
 
2.6%
Other values (59) 114444
29.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 382881
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 42406
 
11.1%
39391
 
10.3%
t 37639
 
9.8%
n 36282
 
9.5%
r 29477
 
7.7%
i 21411
 
5.6%
o 20202
 
5.3%
a 20053
 
5.2%
s 11795
 
3.1%
d 9781
 
2.6%
Other values (59) 114444
29.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 382881
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 42406
 
11.1%
39391
 
10.3%
t 37639
 
9.8%
n 36282
 
9.5%
r 29477
 
7.7%
i 21411
 
5.6%
o 20202
 
5.3%
a 20053
 
5.2%
s 11795
 
3.1%
d 9781
 
2.6%
Other values (59) 114444
29.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 382881
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 42406
 
11.1%
39391
 
10.3%
t 37639
 
9.8%
n 36282
 
9.5%
r 29477
 
7.7%
i 21411
 
5.6%
o 20202
 
5.3%
a 20053
 
5.2%
s 11795
 
3.1%
d 9781
 
2.6%
Other values (59) 114444
29.9%
Distinct15
Distinct (%)1.0%
Missing605332
Missing (%)99.8%
Memory size4.6 MiB
2025-03-26T16:20:33.730286image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length9
Mean length5.811805556
Min length2

Characters and Unicode

Total characters8369
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st rownear
2nd rowuncertain
3rd rownear
4th rownear
5th rowcf.
ValueCountFrequency (%)
near 468
31.7%
uncertain 460
31.2%
cf 238
16.1%
group 113
 
7.7%
subgroup 80
 
5.4%
complex 26
 
1.8%
aff 21
 
1.4%
sp 21
 
1.4%
n 15
 
1.0%
sensu 11
 
0.7%
Other values (5) 23
 
1.6%
2025-03-26T16:20:33.816587image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 1422
17.0%
r 1134
13.6%
e 965
11.5%
a 950
11.4%
u 744
8.9%
c 733
8.8%
t 482
 
5.8%
i 471
 
5.6%
f 280
 
3.3%
p 240
 
2.9%
Other values (12) 948
11.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8369
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 1422
17.0%
r 1134
13.6%
e 965
11.5%
a 950
11.4%
u 744
8.9%
c 733
8.8%
t 482
 
5.8%
i 471
 
5.6%
f 280
 
3.3%
p 240
 
2.9%
Other values (12) 948
11.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8369
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 1422
17.0%
r 1134
13.6%
e 965
11.5%
a 950
11.4%
u 744
8.9%
c 733
8.8%
t 482
 
5.8%
i 471
 
5.6%
f 280
 
3.3%
p 240
 
2.9%
Other values (12) 948
11.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8369
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 1422
17.0%
r 1134
13.6%
e 965
11.5%
a 950
11.4%
u 744
8.9%
c 733
8.8%
t 482
 
5.8%
i 471
 
5.6%
f 280
 
3.3%
p 240
 
2.9%
Other values (12) 948
11.3%

typeStatus
Text

Missing 

Distinct62
Distinct (%)0.1%
Missing487787
Missing (%)80.4%
Memory size4.6 MiB
2025-03-26T16:20:33.846237image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length28
Median length8
Mean length7.058696474
Min length1

Characters and Unicode

Total characters839879
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)< 0.1%

Sample

1st rowParatype
2nd rowType
3rd rowHolotype
4th rowType
5th rowPrimary Syntype
ValueCountFrequency (%)
holotype 54312
44.3%
type 33093
27.0%
syntype 13204
 
10.8%
paratype 11065
 
9.0%
lectotype 5265
 
4.3%
primary 3234
 
2.6%
allotype 1094
 
0.9%
syntypes 430
 
0.4%
neotype 316
 
0.3%
cotype 298
 
0.2%
Other values (14) 175
 
0.1%
2025-03-26T16:20:33.935654image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
y 136106
16.2%
e 124955
14.9%
p 119248
14.2%
o 115767
13.8%
t 91536
10.9%
l 56634
6.7%
H 54315
 
6.5%
T 33100
 
3.9%
a 25641
 
3.1%
r 17670
 
2.1%
Other values (16) 64907
7.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 839879
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
y 136106
16.2%
e 124955
14.9%
p 119248
14.2%
o 115767
13.8%
t 91536
10.9%
l 56634
6.7%
H 54315
 
6.5%
T 33100
 
3.9%
a 25641
 
3.1%
r 17670
 
2.1%
Other values (16) 64907
7.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 839879
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
y 136106
16.2%
e 124955
14.9%
p 119248
14.2%
o 115767
13.8%
t 91536
10.9%
l 56634
6.7%
H 54315
 
6.5%
T 33100
 
3.9%
a 25641
 
3.1%
r 17670
 
2.1%
Other values (16) 64907
7.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 839879
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
y 136106
16.2%
e 124955
14.9%
p 119248
14.2%
o 115767
13.8%
t 91536
10.9%
l 56634
6.7%
H 54315
 
6.5%
T 33100
 
3.9%
a 25641
 
3.1%
r 17670
 
2.1%
Other values (16) 64907
7.7%

identifiedBy
Text

Missing 

Distinct2739
Distinct (%)1.8%
Missing456553
Missing (%)75.2%
Memory size4.6 MiB
2025-03-26T16:20:34.065414image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length150
Median length106
Mean length27.79452666
Min length2

Characters and Unicode

Total characters4175266
Distinct characters71
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique935 ?
Unique (%)0.6%

Sample

1st rowWestfall, M. J., Jr.
2nd rowDonnelly, Thomas W.
3rd rowFlint, Oliver S., Jr., (ENT), Smithsonian Institution - National Museum of Natural History (UNITED STATES)
4th rowKormann, K.
5th rowDeMarmels
ValueCountFrequency (%)
w 28240
 
4.4%
united 24502
 
3.8%
states 24501
 
3.8%
22821
 
3.5%
of 22080
 
3.4%
s 21994
 
3.4%
smithsonian 21991
 
3.4%
institution 21991
 
3.4%
museum 21446
 
3.3%
natural 21166
 
3.3%
Other values (2402) 414545
64.2%
2025-03-26T16:20:34.289223image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
495058
 
11.9%
i 251900
 
6.0%
o 232812
 
5.6%
t 231761
 
5.6%
n 231324
 
5.5%
a 201108
 
4.8%
, 194246
 
4.7%
r 183494
 
4.4%
. 170956
 
4.1%
s 167537
 
4.0%
Other values (61) 1815070
43.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4175266
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
495058
 
11.9%
i 251900
 
6.0%
o 232812
 
5.6%
t 231761
 
5.6%
n 231324
 
5.5%
a 201108
 
4.8%
, 194246
 
4.7%
r 183494
 
4.4%
. 170956
 
4.1%
s 167537
 
4.0%
Other values (61) 1815070
43.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4175266
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
495058
 
11.9%
i 251900
 
6.0%
o 232812
 
5.6%
t 231761
 
5.6%
n 231324
 
5.5%
a 201108
 
4.8%
, 194246
 
4.7%
r 183494
 
4.4%
. 170956
 
4.1%
s 167537
 
4.0%
Other values (61) 1815070
43.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4175266
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
495058
 
11.9%
i 251900
 
6.0%
o 232812
 
5.6%
t 231761
 
5.6%
n 231324
 
5.5%
a 201108
 
4.8%
, 194246
 
4.7%
r 183494
 
4.4%
. 170956
 
4.1%
s 167537
 
4.0%
Other values (61) 1815070
43.5%
Distinct245755
Distinct (%)40.8%
Missing4648
Missing (%)0.8%
Memory size4.6 MiB
2025-03-26T16:20:34.491174image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length68
Median length61
Mean length20.77020514
Min length3

Characters and Unicode

Total characters12506239
Distinct characters82
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique201901 ?
Unique (%)33.5%

Sample

1st rowCamponotus (Myrmosericus) rufoglaucus cinctella var. rufigenis
2nd rowAthrips mesoleuca
3rd rowParanthrene asilipennis
4th rowAcanthagrion trilobatum
5th rowCalathus nanulus
ValueCountFrequency (%)
bombus 69822
 
5.3%
sp 44550
 
3.4%
pyrobombus 21315
 
1.6%
xylocopa 12270
 
0.9%
unidentified 9054
 
0.7%
argia 8699
 
0.7%
apis 8630
 
0.6%
crambus 8000
 
0.6%
enallagma 8000
 
0.6%
ischnura 7488
 
0.6%
Other values (131051) 1131253
85.1%
2025-03-26T16:20:34.766264image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1258350
 
10.1%
i 1046811
 
8.4%
s 974706
 
7.8%
o 845695
 
6.8%
e 823788
 
6.6%
726957
 
5.8%
r 715134
 
5.7%
l 625295
 
5.0%
u 617044
 
4.9%
n 591871
 
4.7%
Other values (72) 4280588
34.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 12506239
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1258350
 
10.1%
i 1046811
 
8.4%
s 974706
 
7.8%
o 845695
 
6.8%
e 823788
 
6.6%
726957
 
5.8%
r 715134
 
5.7%
l 625295
 
5.0%
u 617044
 
4.9%
n 591871
 
4.7%
Other values (72) 4280588
34.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 12506239
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1258350
 
10.1%
i 1046811
 
8.4%
s 974706
 
7.8%
o 845695
 
6.8%
e 823788
 
6.6%
726957
 
5.8%
r 715134
 
5.7%
l 625295
 
5.0%
u 617044
 
4.9%
n 591871
 
4.7%
Other values (72) 4280588
34.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 12506239
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1258350
 
10.1%
i 1046811
 
8.4%
s 974706
 
7.8%
o 845695
 
6.8%
e 823788
 
6.6%
726957
 
5.8%
r 715134
 
5.7%
l 625295
 
5.0%
u 617044
 
4.9%
n 591871
 
4.7%
Other values (72) 4280588
34.2%
Distinct3456
Distinct (%)0.6%
Missing4667
Missing (%)0.8%
Memory size4.6 MiB
2025-03-26T16:20:34.811063image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length97
Median length91
Mean length62.39118758
Min length9

Characters and Unicode

Total characters37566046
Distinct characters61
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique574 ?
Unique (%)0.1%

Sample

1st rowAnimalia, Arthropoda, Insecta, Hymenoptera, Formicidae, Formicinae
2nd rowAnimalia, Arthropoda, Insecta, Lepidoptera, Gelechiidae, Gelechiinae
3rd rowAnimalia, Arthropoda, Insecta, Lepidoptera, Sesiidae, Sesiinae
4th rowAnimalia, Arthropoda, Insecta, Odonata, Zygoptera, Coenagrionidae
5th rowAnimalia, Arthropoda, Insecta, Coleoptera, Carabidae
ValueCountFrequency (%)
arthropoda 601823
17.3%
animalia 600451
17.3%
insecta 590003
17.0%
hymenoptera 147015
 
4.2%
odonata 117708
 
3.4%
lepidoptera 100292
 
2.9%
apidae 83219
 
2.4%
diptera 73816
 
2.1%
coleoptera 72332
 
2.1%
apinae 63734
 
1.8%
Other values (2936) 1029670
29.6%
2025-03-26T16:20:34.916571image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 4586972
12.2%
e 2948644
 
7.8%
2877958
 
7.7%
, 2877592
 
7.7%
i 2875255
 
7.7%
o 2441570
 
6.5%
r 2325014
 
6.2%
t 2199825
 
5.9%
n 2167750
 
5.8%
p 1696131
 
4.5%
Other values (51) 10569335
28.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 37566046
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 4586972
12.2%
e 2948644
 
7.8%
2877958
 
7.7%
, 2877592
 
7.7%
i 2875255
 
7.7%
o 2441570
 
6.5%
r 2325014
 
6.2%
t 2199825
 
5.9%
n 2167750
 
5.8%
p 1696131
 
4.5%
Other values (51) 10569335
28.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 37566046
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 4586972
12.2%
e 2948644
 
7.8%
2877958
 
7.7%
, 2877592
 
7.7%
i 2875255
 
7.7%
o 2441570
 
6.5%
r 2325014
 
6.2%
t 2199825
 
5.9%
n 2167750
 
5.8%
p 1696131
 
4.5%
Other values (51) 10569335
28.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 37566046
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 4586972
12.2%
e 2948644
 
7.8%
2877958
 
7.7%
, 2877592
 
7.7%
i 2875255
 
7.7%
o 2441570
 
6.5%
r 2325014
 
6.2%
t 2199825
 
5.9%
n 2167750
 
5.8%
p 1696131
 
4.5%
Other values (51) 10569335
28.1%

kingdom
Text

Constant  Missing 

Distinct1
Distinct (%)< 0.1%
Missing6321
Missing (%)1.0%
Memory size4.6 MiB
2025-03-26T16:20:34.944575image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters4803608
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAnimalia
2nd rowAnimalia
3rd rowAnimalia
4th rowAnimalia
5th rowAnimalia
ValueCountFrequency (%)
animalia 600451
100.0%
2025-03-26T16:20:35.023024image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 1200902
25.0%
a 1200902
25.0%
A 600451
12.5%
n 600451
12.5%
m 600451
12.5%
l 600451
12.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4803608
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 1200902
25.0%
a 1200902
25.0%
A 600451
12.5%
n 600451
12.5%
m 600451
12.5%
l 600451
12.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4803608
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 1200902
25.0%
a 1200902
25.0%
A 600451
12.5%
n 600451
12.5%
m 600451
12.5%
l 600451
12.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4803608
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 1200902
25.0%
a 1200902
25.0%
A 600451
12.5%
n 600451
12.5%
m 600451
12.5%
l 600451
12.5%

phylum
Text

Distinct2
Distinct (%)< 0.1%
Missing4949
Missing (%)0.8%
Memory size4.6 MiB
2025-03-26T16:20:35.049352image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters6018230
Distinct characters8
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowArthropoda
2nd rowArthropoda
3rd rowArthropoda
4th rowArthropoda
5th rowArthropoda
ValueCountFrequency (%)
arthropoda 601823
100.0%
2025-03-26T16:20:35.125217image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
r 1203646
20.0%
o 1203646
20.0%
a 601859
10.0%
t 601823
10.0%
h 601823
10.0%
p 601823
10.0%
d 601823
10.0%
A 601787
10.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6018230
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
r 1203646
20.0%
o 1203646
20.0%
a 601859
10.0%
t 601823
10.0%
h 601823
10.0%
p 601823
10.0%
d 601823
10.0%
A 601787
10.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6018230
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
r 1203646
20.0%
o 1203646
20.0%
a 601859
10.0%
t 601823
10.0%
h 601823
10.0%
p 601823
10.0%
d 601823
10.0%
A 601787
10.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6018230
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
r 1203646
20.0%
o 1203646
20.0%
a 601859
10.0%
t 601823
10.0%
h 601823
10.0%
p 601823
10.0%
d 601823
10.0%
A 601787
10.0%

class
Text

Distinct13
Distinct (%)< 0.1%
Missing5514
Missing (%)0.9%
Memory size4.6 MiB
2025-03-26T16:20:35.152990image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length12
Median length7
Mean length7.038306351
Min length7

Characters and Unicode

Total characters4231838
Distinct characters28
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowInsecta
2nd rowInsecta
3rd rowInsecta
4th rowInsecta
5th rowInsecta
ValueCountFrequency (%)
insecta 590003
98.1%
arachnida 7933
 
1.3%
diplopoda 1612
 
0.3%
collembola 801
 
0.1%
chilopoda 741
 
0.1%
diplura 76
 
< 0.1%
protura 63
 
< 0.1%
symphyla 8
 
< 0.1%
myriapoda 6
 
< 0.1%
onychophora 6
 
< 0.1%
Other values (3) 9
 
< 0.1%
2025-03-26T16:20:35.308043image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 609200
14.4%
n 597954
14.1%
c 597944
14.1%
e 590804
14.0%
t 590067
13.9%
s 590004
13.9%
I 590003
13.9%
i 10368
 
0.2%
d 10296
 
0.2%
h 8694
 
0.2%
Other values (18) 36504
 
0.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4231838
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 609200
14.4%
n 597954
14.1%
c 597944
14.1%
e 590804
14.0%
t 590067
13.9%
s 590004
13.9%
I 590003
13.9%
i 10368
 
0.2%
d 10296
 
0.2%
h 8694
 
0.2%
Other values (18) 36504
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4231838
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 609200
14.4%
n 597954
14.1%
c 597944
14.1%
e 590804
14.0%
t 590067
13.9%
s 590004
13.9%
I 590003
13.9%
i 10368
 
0.2%
d 10296
 
0.2%
h 8694
 
0.2%
Other values (18) 36504
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4231838
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 609200
14.4%
n 597954
14.1%
c 597944
14.1%
e 590804
14.0%
t 590067
13.9%
s 590004
13.9%
I 590003
13.9%
i 10368
 
0.2%
d 10296
 
0.2%
h 8694
 
0.2%
Other values (18) 36504
 
0.9%

order
Text

Distinct85
Distinct (%)< 0.1%
Missing4834
Missing (%)0.8%
Memory size4.6 MiB
2025-03-26T16:20:35.344242image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length16
Mean length9.460834837
Min length5

Characters and Unicode

Total characters5694836
Distinct characters43
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowHymenoptera
2nd rowLepidoptera
3rd rowLepidoptera
4th rowOdonata
5th rowColeoptera
ValueCountFrequency (%)
hymenoptera 146926
24.4%
odonata 117708
19.6%
lepidoptera 100266
16.7%
diptera 73811
12.3%
coleoptera 72320
12.0%
hemiptera 37882
 
6.3%
siphonaptera 10121
 
1.7%
trichoptera 9143
 
1.5%
araneae 4659
 
0.8%
thysanoptera 4639
 
0.8%
Other values (73) 24463
 
4.1%
2025-03-26T16:20:35.435635image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 852483
15.0%
a 750503
13.2%
t 602188
10.6%
p 585281
10.3%
o 556588
9.8%
r 498170
8.7%
n 285685
 
5.0%
i 242627
 
4.3%
d 223949
 
3.9%
m 191272
 
3.4%
Other values (33) 906090
15.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5694836
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 852483
15.0%
a 750503
13.2%
t 602188
10.6%
p 585281
10.3%
o 556588
9.8%
r 498170
8.7%
n 285685
 
5.0%
i 242627
 
4.3%
d 223949
 
3.9%
m 191272
 
3.4%
Other values (33) 906090
15.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5694836
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 852483
15.0%
a 750503
13.2%
t 602188
10.6%
p 585281
10.3%
o 556588
9.8%
r 498170
8.7%
n 285685
 
5.0%
i 242627
 
4.3%
d 223949
 
3.9%
m 191272
 
3.4%
Other values (33) 906090
15.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5694836
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 852483
15.0%
a 750503
13.2%
t 602188
10.6%
p 585281
10.3%
o 556588
9.8%
r 498170
8.7%
n 285685
 
5.0%
i 242627
 
4.3%
d 223949
 
3.9%
m 191272
 
3.4%
Other values (33) 906090
15.9%

family
Text

Distinct1481
Distinct (%)0.2%
Missing4956
Missing (%)0.8%
Memory size4.6 MiB
2025-03-26T16:20:35.556000image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length22
Median length19
Mean length10.51253207
Min length3

Characters and Unicode

Total characters6326610
Distinct characters59
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique207 ?
Unique (%)< 0.1%

Sample

1st rowFormicidae
2nd rowGelechiidae
3rd rowSesiidae
4th rowCoenagrionidae
5th rowCarabidae
ValueCountFrequency (%)
apidae 83219
 
13.8%
libellulidae 42649
 
7.1%
coenagrionidae 35308
 
5.9%
chrysomelidae 17589
 
2.9%
asilidae 13455
 
2.2%
geometridae 12814
 
2.1%
crambidae 12133
 
2.0%
curculionidae 12064
 
2.0%
psychodidae 11823
 
2.0%
formicidae 9961
 
1.7%
Other values (1470) 351166
58.3%
2025-03-26T16:20:35.760608image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 916458
14.5%
e 891643
14.1%
a 820926
13.0%
d 672868
10.6%
o 327328
 
5.2%
l 322216
 
5.1%
r 289665
 
4.6%
p 213595
 
3.4%
n 210262
 
3.3%
h 149915
 
2.4%
Other values (49) 1511734
23.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6326610
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 916458
14.5%
e 891643
14.1%
a 820926
13.0%
d 672868
10.6%
o 327328
 
5.2%
l 322216
 
5.1%
r 289665
 
4.6%
p 213595
 
3.4%
n 210262
 
3.3%
h 149915
 
2.4%
Other values (49) 1511734
23.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6326610
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 916458
14.5%
e 891643
14.1%
a 820926
13.0%
d 672868
10.6%
o 327328
 
5.2%
l 322216
 
5.1%
r 289665
 
4.6%
p 213595
 
3.4%
n 210262
 
3.3%
h 149915
 
2.4%
Other values (49) 1511734
23.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6326610
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 916458
14.5%
e 891643
14.1%
a 820926
13.0%
d 672868
10.6%
o 327328
 
5.2%
l 322216
 
5.1%
r 289665
 
4.6%
p 213595
 
3.4%
n 210262
 
3.3%
h 149915
 
2.4%
Other values (49) 1511734
23.9%

genus
Text

Distinct39792
Distinct (%)6.6%
Missing5451
Missing (%)0.9%
Memory size4.6 MiB
2025-03-26T16:20:35.910767image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length21
Mean length8.981099945
Min length1

Characters and Unicode

Total characters5400524
Distinct characters73
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14847 ?
Unique (%)2.5%

Sample

1st rowCamponotus
2nd rowAthrips
3rd rowParanthrene
4th rowAcanthagrion
5th rowCalathus
ValueCountFrequency (%)
bombus 62580
 
10.4%
xylocopa 12151
 
2.0%
unidentified 8832
 
1.5%
argia 8696
 
1.4%
crambus 8000
 
1.3%
enallagma 8000
 
1.3%
ischnura 7488
 
1.2%
sympetrum 6048
 
1.0%
apis 4985
 
0.8%
lestes 4259
 
0.7%
Other values (39738) 470382
78.2%
2025-03-26T16:20:36.126492image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 532576
 
9.9%
o 473552
 
8.8%
i 399947
 
7.4%
s 399684
 
7.4%
e 382267
 
7.1%
r 325237
 
6.0%
l 256935
 
4.8%
u 249197
 
4.6%
t 243881
 
4.5%
m 235251
 
4.4%
Other values (63) 1901997
35.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5400524
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 532576
 
9.9%
o 473552
 
8.8%
i 399947
 
7.4%
s 399684
 
7.4%
e 382267
 
7.1%
r 325237
 
6.0%
l 256935
 
4.8%
u 249197
 
4.6%
t 243881
 
4.5%
m 235251
 
4.4%
Other values (63) 1901997
35.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5400524
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 532576
 
9.9%
o 473552
 
8.8%
i 399947
 
7.4%
s 399684
 
7.4%
e 382267
 
7.1%
r 325237
 
6.0%
l 256935
 
4.8%
u 249197
 
4.6%
t 243881
 
4.5%
m 235251
 
4.4%
Other values (63) 1901997
35.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5400524
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 532576
 
9.9%
o 473552
 
8.8%
i 399947
 
7.4%
s 399684
 
7.4%
e 382267
 
7.1%
r 325237
 
6.0%
l 256935
 
4.8%
u 249197
 
4.6%
t 243881
 
4.5%
m 235251
 
4.4%
Other values (63) 1901997
35.2%

subgenus
Text

Missing 

Distinct3173
Distinct (%)3.4%
Missing514262
Missing (%)84.8%
Memory size4.6 MiB
2025-03-26T16:20:36.174941image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length18
Mean length9.946621987
Min length1

Characters and Unicode

Total characters920162
Distinct characters57
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1135 ?
Unique (%)1.2%

Sample

1st rowMyrmosericus
2nd rowAnomalagrion
3rd rowAnomalagrion
4th rowHypocaccus
5th rowBombus
ValueCountFrequency (%)
pyrobombus 21314
23.0%
bombus 7242
 
7.8%
apis 3644
 
3.9%
fervidobombus 3302
 
3.6%
neoxylocopa 2436
 
2.6%
alpinobombus 1562
 
1.7%
xylocopoides 1498
 
1.6%
schonnherria 1464
 
1.6%
separatobombus 1330
 
1.4%
chimarra 1298
 
1.4%
Other values (3162) 47441
51.3%
2025-03-26T16:20:36.272673image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 129838
14.1%
s 74194
 
8.1%
b 73720
 
8.0%
r 63311
 
6.9%
m 58354
 
6.3%
u 58009
 
6.3%
a 57660
 
6.3%
i 52342
 
5.7%
y 39920
 
4.3%
e 39600
 
4.3%
Other values (47) 273214
29.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 920162
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 129838
14.1%
s 74194
 
8.1%
b 73720
 
8.0%
r 63311
 
6.9%
m 58354
 
6.3%
u 58009
 
6.3%
a 57660
 
6.3%
i 52342
 
5.7%
y 39920
 
4.3%
e 39600
 
4.3%
Other values (47) 273214
29.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 920162
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 129838
14.1%
s 74194
 
8.1%
b 73720
 
8.0%
r 63311
 
6.9%
m 58354
 
6.3%
u 58009
 
6.3%
a 57660
 
6.3%
i 52342
 
5.7%
y 39920
 
4.3%
e 39600
 
4.3%
Other values (47) 273214
29.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 920162
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 129838
14.1%
s 74194
 
8.1%
b 73720
 
8.0%
r 63311
 
6.9%
m 58354
 
6.3%
u 58009
 
6.3%
a 57660
 
6.3%
i 52342
 
5.7%
y 39920
 
4.3%
e 39600
 
4.3%
Other values (47) 273214
29.7%

specificEpithet
Text

Missing 

Distinct89118
Distinct (%)14.9%
Missing8782
Missing (%)1.4%
Memory size4.6 MiB
2025-03-26T16:20:36.420720image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length25
Mean length8.29383769
Min length1

Characters and Unicode

Total characters4959632
Distinct characters53
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50182 ?
Unique (%)8.4%

Sample

1st rowrufoglaucus
2nd rowmesoleuca
3rd rowasilipennis
4th rowtrilobatum
5th rownanulus
ValueCountFrequency (%)
sp 44550
 
7.4%
sylvicola 6306
 
1.1%
bifarius 4095
 
0.7%
kirbyellus 3629
 
0.6%
flavifrons 3495
 
0.6%
impatiens 3148
 
0.5%
undetermined 3060
 
0.5%
nevadensis 2532
 
0.4%
cerana 2438
 
0.4%
affinis 2303
 
0.4%
Other values (88974) 523066
87.4%
2025-03-26T16:20:36.657137image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 626268
12.6%
i 558565
11.3%
s 473415
 
9.5%
e 379043
 
7.6%
n 325437
 
6.6%
l 325134
 
6.6%
r 302717
 
6.1%
u 290510
 
5.9%
t 261879
 
5.3%
c 232431
 
4.7%
Other values (43) 1184233
23.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4959632
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 626268
12.6%
i 558565
11.3%
s 473415
 
9.5%
e 379043
 
7.6%
n 325437
 
6.6%
l 325134
 
6.6%
r 302717
 
6.1%
u 290510
 
5.9%
t 261879
 
5.3%
c 232431
 
4.7%
Other values (43) 1184233
23.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4959632
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 626268
12.6%
i 558565
11.3%
s 473415
 
9.5%
e 379043
 
7.6%
n 325437
 
6.6%
l 325134
 
6.6%
r 302717
 
6.1%
u 290510
 
5.9%
t 261879
 
5.3%
c 232431
 
4.7%
Other values (43) 1184233
23.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4959632
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 626268
12.6%
i 558565
11.3%
s 473415
 
9.5%
e 379043
 
7.6%
n 325437
 
6.6%
l 325134
 
6.6%
r 302717
 
6.1%
u 290510
 
5.9%
t 261879
 
5.3%
c 232431
 
4.7%
Other values (43) 1184233
23.9%

infraspecificEpithet
Text

Missing 

Distinct8367
Distinct (%)24.9%
Missing573171
Missing (%)94.5%
Memory size4.6 MiB
2025-03-26T16:20:36.801958image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length36
Median length22
Mean length8.847415255
Min length1

Characters and Unicode

Total characters297282
Distinct characters38
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5811 ?
Unique (%)17.3%

Sample

1st rowrufigenis
2nd rowdecrescens
3rd rowmarianae
4th rowneglectum
5th rowlavatus
ValueCountFrequency (%)
nearcticus 2537
 
7.5%
fervidus 1190
 
3.5%
violacea 993
 
3.0%
pensylvanicus 905
 
2.7%
vagans 877
 
2.6%
portia 726
 
2.2%
virginica 595
 
1.8%
auricormus 587
 
1.7%
auripennis 578
 
1.7%
dorsata 442
 
1.3%
Other values (8347) 24222
72.0%
2025-03-26T16:20:37.009102image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 39096
13.2%
i 34722
11.7%
s 26812
9.0%
n 23090
 
7.8%
r 21623
 
7.3%
e 21467
 
7.2%
u 19068
 
6.4%
c 18379
 
6.2%
t 14624
 
4.9%
o 13909
 
4.7%
Other values (28) 64492
21.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 297282
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 39096
13.2%
i 34722
11.7%
s 26812
9.0%
n 23090
 
7.8%
r 21623
 
7.3%
e 21467
 
7.2%
u 19068
 
6.4%
c 18379
 
6.2%
t 14624
 
4.9%
o 13909
 
4.7%
Other values (28) 64492
21.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 297282
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 39096
13.2%
i 34722
11.7%
s 26812
9.0%
n 23090
 
7.8%
r 21623
 
7.3%
e 21467
 
7.2%
u 19068
 
6.4%
c 18379
 
6.2%
t 14624
 
4.9%
o 13909
 
4.7%
Other values (28) 64492
21.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 297282
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 39096
13.2%
i 34722
11.7%
s 26812
9.0%
n 23090
 
7.8%
r 21623
 
7.3%
e 21467
 
7.2%
u 19068
 
6.4%
c 18379
 
6.2%
t 14624
 
4.9%
o 13909
 
4.7%
Other values (28) 64492
21.7%

taxonRank
Text

Missing 

Distinct17
Distinct (%)0.1%
Missing573176
Missing (%)94.5%
Memory size4.6 MiB
2025-03-26T16:20:37.046181image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length17
Median length10
Mean length9.835784022
Min length4

Characters and Unicode

Total characters330443
Distinct characters30
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowVariety
2nd rowsubspecies
3rd rowsubspecies
4th rowsubspecies
5th rowsubspecies
ValueCountFrequency (%)
subspecies 31707
94.3%
variety 1486
 
4.4%
aberration 168
 
0.5%
form 105
 
0.3%
race 70
 
0.2%
morphotype 28
 
0.1%
species 10
 
< 0.1%
group 10
 
< 0.1%
undet.cat 9
 
< 0.1%
var 5
 
< 0.1%
Other values (4) 10
 
< 0.1%
2025-03-26T16:20:37.129483image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 95144
28.8%
e 65195
19.7%
i 33383
 
10.1%
b 31875
 
9.6%
p 31788
 
9.6%
c 31787
 
9.6%
u 31717
 
9.6%
r 1990
 
0.6%
a 1749
 
0.5%
t 1709
 
0.5%
Other values (20) 4106
 
1.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 330443
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 95144
28.8%
e 65195
19.7%
i 33383
 
10.1%
b 31875
 
9.6%
p 31788
 
9.6%
c 31787
 
9.6%
u 31717
 
9.6%
r 1990
 
0.6%
a 1749
 
0.5%
t 1709
 
0.5%
Other values (20) 4106
 
1.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 330443
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 95144
28.8%
e 65195
19.7%
i 33383
 
10.1%
b 31875
 
9.6%
p 31788
 
9.6%
c 31787
 
9.6%
u 31717
 
9.6%
r 1990
 
0.6%
a 1749
 
0.5%
t 1709
 
0.5%
Other values (20) 4106
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 330443
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 95144
28.8%
e 65195
19.7%
i 33383
 
10.1%
b 31875
 
9.6%
p 31788
 
9.6%
c 31787
 
9.6%
u 31717
 
9.6%
r 1990
 
0.6%
a 1749
 
0.5%
t 1709
 
0.5%
Other values (20) 4106
 
1.2%
Distinct10009
Distinct (%)1.9%
Missing90810
Missing (%)15.0%
Memory size4.6 MiB
2025-03-26T16:20:37.259410image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length43
Median length33
Mean length7.761711134
Min length2

Characters and Unicode

Total characters4004748
Distinct characters83
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3229 ?
Unique (%)0.6%

Sample

1st rowForel
2nd row(Lower)
3rd row(Guérin-Méneville)
4th rowLeonard
5th rowCasey
ValueCountFrequency (%)
25884
 
4.4%
hagen 24669
 
4.1%
cresson 22247
 
3.7%
selys 21399
 
3.6%
casey 19813
 
3.3%
say 14287
 
2.4%
fabricius 14023
 
2.4%
alexander 9951
 
1.7%
smith 9622
 
1.6%
kirby 8939
 
1.5%
Other values (6012) 423806
71.3%
2025-03-26T16:20:37.464482image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 429365
 
10.7%
a 307495
 
7.7%
r 299146
 
7.5%
n 242739
 
6.1%
s 235625
 
5.9%
i 207942
 
5.2%
l 196189
 
4.9%
o 173078
 
4.3%
( 140753
 
3.5%
) 140753
 
3.5%
Other values (73) 1631663
40.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4004748
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 429365
 
10.7%
a 307495
 
7.7%
r 299146
 
7.5%
n 242739
 
6.1%
s 235625
 
5.9%
i 207942
 
5.2%
l 196189
 
4.9%
o 173078
 
4.3%
( 140753
 
3.5%
) 140753
 
3.5%
Other values (73) 1631663
40.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4004748
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 429365
 
10.7%
a 307495
 
7.7%
r 299146
 
7.5%
n 242739
 
6.1%
s 235625
 
5.9%
i 207942
 
5.2%
l 196189
 
4.9%
o 173078
 
4.3%
( 140753
 
3.5%
) 140753
 
3.5%
Other values (73) 1631663
40.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4004748
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 429365
 
10.7%
a 307495
 
7.7%
r 299146
 
7.5%
n 242739
 
6.1%
s 235625
 
5.9%
i 207942
 
5.2%
l 196189
 
4.9%
o 173078
 
4.3%
( 140753
 
3.5%
) 140753
 
3.5%
Other values (73) 1631663
40.7%